Author Archives: M&MDaclan

Dandansoy: A Visayan Folk Song

Dandansoy is the name of a boy. This song is about the singer leaving Dandansoy to go back to her hometown.

 

 

To Honor a Friend: Hilaria Catayas – Aldema

Farewell mamoLar
[Laria Catayas-Aldema]

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Right now I can imagine your hug
I grieve of your passing ateLaria
Yet I feel you console me instead
Those hands so firm yet gentle
On warm and assuring massage

Oh you’re supposed to be fifty-three
In two days, on November three
So you’ll celebrate your birthday
Up there where there’s no pain
Up where there’s eternal rest

For most of your living years
In a big family of nine as eldest
No memo for such familial role
Yet acted as breadwinner for all
Sent younger siblings to school

Oh how simple our life was in IH
No internet yet to eat our time away
So we had more time for camaraderie
Cooking our all-time favorite paksiw
Watching TV with just one channel

You’re in my memorable life events
On my wedding as candle sponsor
Even Kim’s monthly photography
Sponsored cake for Johm’s birthday
A mamo to Sam as our shared baby

So it was such an honor for us
When you chose us as your witness
In a civil rite before church ceremony
There we went on our humble jeepey
And celebrate over a meal in the city

Thank you ate Laria for all those
Encouraging eldest experiences
For if you bore it with eight sibs
There’s no reason I can’t with five
Thank you for all those joyous days

Farewell and have your eternal rest

*picture above from Kim’s First Year photo album

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Dear Timothé: As a Nephew Turns Two

PhotoGrid_1508673803750.jpgHow glad we are
To be able to hug you
For real each year
To get to know you
For weeks is rare
To see what you eat
How you sleep
Know your favorites

Indeed to be in Pinas
For overseas pinoys
Is beyond a decision
It’s a commitment
Your dad had made
With your papaLo daw
For your mom to see
Once a year her family

God bless you Timothé
And your loving family
You’re so blessed with
Marvelous papâ et mamâ
Who value relationships
Hardwork and service
Who go out of their way
To make others feel okay

Thanks to technology
That at such young age
We get to see you bake
In the Crèche with granny
And smell various herbs
Oh how so wonderful!
Such learning environ
Stay smiling Timothé

#pamangkin4ofSoon7

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Ashitaba Leaves: Edible and Wonderful

To be packed with much properties alledged to be beneficial to human health is just too wonderful for a leaf! And because the leaf comes from a plant that has grown and been used by Japanese since when makes it more believable.

And why not? Japanese people are amongst those with highest life expectancy in the planet earth (Population Reference Bureau 2016). When a group of humans live ten to twenty years more than the rest in the same universe, they must have something that the rest do not have. They must have better environment, better peace and order, healthier food, more positive outlook in life, happier relationships, more resilience and more.

So, let us get back to Ashitaba leaves. I am a fortunate recipient of Ashitaba plant from a classmate-friend Jenny who lives in a cool, farm-conducive, mountainous Bukidnon. Bukidnon province is one of the vegetable baskets of the Philippines. I did not know about Ashitaba but this friend’s generosity led me to it. Jenny knows I am a natural remedy advocate. With my husband’s help (in getting good soil), our home is now with this Japanese plant Ashitaba.

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In more complex but delicious taste, the leaves can be taken in as a juice, smoothie, tea or salad dressing. For no hassle, simply pluck a leaf, wash and eat!

My son has this eating vegetable challenge in his health class today. The easiest and fastest way is to cut three tip branches from the Ashitaba plant and voila! Johm has now the ready to eat veggie. Off to school he went this morning with these leaves still on the tip branches inside a clear plastic food container.

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So, what are those alledge health benefits of Ashitaba leaves? Here is a good write-up about Ashitaba from Ashitaba Plant website.

What Is Ashitaba

Ashitaba has the scientific name Angelica Keiskei. This plant naturally grows on coastal lands in Japan (here is in depth article about growing ashitaba). Ashitaba has been a staple in the Japanese diet and “regular” in their medicine cabinets for centuries. Recently, Ashitaba has begun to grace in natural food stores and on the worldwide web.

Based on folktales, the Japanese have used Ashitaba for generations. Only in the 90s that modern researchers—hearing of its benefits —dig deeper about the plant.

Scientific Researches on Ashitaba

In 1991, Y. Inamori and his group of scientists from Osaka University in Japan set out to find what was so magical about the plant. They were specifically studying “chalcones”—naturally occurring antioxidants found in the plant that provide the medicinal properties.

Inamori’s research was focused on two specific chalcones (xanthoangelol and 4-hydroxyderricin) which he isolated because they were thought to provide powerful anti-bacterial benefits. The scientists actually used the drug Streptomycin in the study, and compared its potency to Ashitaba. While Streptomycin was more powerful than the plant, they found Ashitaba to be very effective against Staph and Strep infections (and you don’t even need a prescription!).

At the end of the study, the scientists said that Ashitaba “possessed potent anti-bacterial properties.” They concluded by writing, “The growth-inhibitory effects of II [Ashitaba] on plant-pathogenic bacteria is also reported for the first time in this paper.”

Another research group lead by Takata Okuyama from Meiji College in Tokyo, was looking at the anti-tumor benefits of Ashitaba. They were focusing on Ashitaba’s golden, oozing sap that is extremely rich in specific “chalcones”. The scientists stated that potent anti-tumor promoter activity has been found in “extracts of the root of Ashitaba which is eaten as a vegetable in Japan”.

The Meiji College group was focused on two completely different chalcones (xanthoangelol and ashitaba-chalcone). According to their report, both of the chalcones revealed anti-tumor-promoting activity and “may be useful in developing effective methods for cancer prevention.”

Ashitaba can also keep your blood healthy. This, according to Jing-Ping OY, and associates at the Medical College of Wuhan University, Wuhan China. This group of scientists wanted to learn if Ashitaba could protect human endothelial cells. Endothelial cells are cells that line the blood vessels.

They discovered that Ashitaba had anti-atheroscleroticeffects on high cholesterol. In other words, Ashitaba is “heart-protective.” They actually went so far as to write that all the health problems associated with high cholesterol could be “reversed by Ashitaba [angelica] significantly; our findings provided experimental basement for the clinical application of Ashitaba [angelica] to prevent the development of atherosclerosis.”

For this last research group, Wang X and his scientists reported in the Archives of Pharmaceutical Research on findings discovered about the plant. These researchers wanted to know if there was a connection between Ashitaba and blood circulation. The scientists placed red blood cells (RBCs) in various concentrations of Ashitaba in test tubes. Their question: Does Ashitaba affect aggregation or “clumping” of red blood cells? (Clumping of blood cells is not good because it can result in strokes and other problems.)

Further, they wanted to know—when Ashitaba was present in the blood— how red blood cells preformed when they were “squeezed” or “squished” as they passed through tiny capillaries in the body (scientists call this deformation, and only healthy red blood cells can withstand the pressure).

Amazingly, the researchers showed that when the chalcones in Ashitaba were present, red blood cells were strengthened, didn’t clump, and could withstand their tight passage through minuscule capillaries. In other words, the blood cells were made stronger. Ashitaba has a “positive effect against certain cardiovascular diseases.”

Welcoming Ashitaba

Knowing all these health benefits, it is just sensible to include Ashitaba in daily regimen. The plant is too gardener-friendly it grows without much effort and hassle. And it tastes alright like other vegetables.

References

Inamori Y, Baba K, Tsujibo H, Taniguchi M, Nakata K, Kozawa M. Antibacterial Activity of Two Chalcones, Xanthoangelol and 4-hydroxyderricin, Isolated from the Root of Angelica Keiskei.
Osaka University of Pharmaceutical Sciences, Japan. Pharmacol Ther 1991 Dec;52(3):331-63.

Jing-Ping OY, Baohua W, Yongming L, Lei W, Jingwei Y Effect Of Angelica On The Expressional Changes Of Cytokines In Endothelial Cells Induced By Hyperlipidemic Serum.Department of Pathophysiology, Medical College of Wuhan University, Wuhan, 430071, P.R. China. hybs@public.wh.hb.cn Clin Hemorheol Microcirc 2001;24(3):201-5.

Wang X, Wei L, Ouyang JP, Muller S, Gentils M, Cauchois G, Stoltz JF. Effects Of An Angelica Extract On Human Erythrocyte Aggregation, Deformation And Osmotic Fragility Group Cell and Tissue Mechanics and Engineering, LEMTA – UMR 7563 CNRS/INPL/UHP, 54500 Vandoeuvre-les- Nancy, France. xwang@ensem.inpl-nancy.fr 1991 Mar;14(1):87-92.

Okuyama T, Takata M, Takayasu J, Hasegawa T, Tokuda H, Nishino A, Nishino H, Iwashima A. Anti- tumor-promotion by principles obtained from Angelica keiskei. Department of Pharmacognosy and Phytochemistry, Meiji College of Pharmacy, Tokyo, Japan. Chem Pharm Bull (Tokyo) 1991 Jun;39(6):1604-5.

Exam Preparations Revisited: Nursing Board Exam as a Springboard for Compre

Since 1978 to this writing (2017), I  have been taking tests and examinations in various formal educational setting. So tests and examinations are like other folkways to me. They are like choosing the best clothes to wear as casual wear or as Sunday’s best. But, there are really big time events, like my wedding, which preparations for the clothes take weeks. And, such clothes are worn only in few hours. Such is the case of a board exam and comprehensive exam!

NLE review.jpgIn March 2009, I graduated from my third course, Bachelor of Science in Nursing at a Seventh Day Adventist health school. This was when my youngest child of three was age 2 years and 3 months. I started the nursing course when my second child was 11 months old. I could say that this student life was intertwined with motherhood and work. Motherhood revolved around a 2 year old, breastfeeding a second child, a pregnancy of third child, another breastfeeding of the third child. Work demands involved commuting from my residence to another city (Marawi City) every day. And, student schedule is everyday after work. This has to be the most complex of all situations I’ve ever been. As in.

And, for the first time there was a board exam I need to pass! I really felt at that time that I do not need a review center to review me. I felt it in my heart that I knew best how to review myself. I believe I am old enough to adhere to my schedule. While a review center’s schedule may not fit my needs. And, it would a waste of my time. I did not have much time. I have already applied for the June 6 and 7 exam dates. The next exam would be by December. Between the two schedules, my heart and mind tell me to grab the June schedule. I have funny but logical reasons. For June exam, I have every reason to fail. Time to review is too short, only from April to May. And, the more if do not review properly in a review center. Just self-review is a ridiculous idea to some. So if I pass, it’s a wondrous outcome! For December exam, I have every reason to pass! So I would have a long review period from April to November. My mind was telling me, should I fail, I definitely cannot accept it. I would be in a fit of a depression, I guess. So, I embarked on the risky, short route.

Because I’ve helped my sister in the final phase of her master’s thesis in April, I’ve started my self review on the third week of April. By then, my husband decided to bring all the three children and himself to his mother’s place. They vacated our home for my solo use. His idea actually, which turned out to be so helpful for me. My sister advised me to enrol in a final coaching review for a week to boast my confidence. So I did enrol myself to a final coaching in another city, in the last week of May. So, I have two weeks in April and three weeks in May. I have a total of 5 weeks before the final coaching.

I gathered all my notes, photocopies, exam papers, case presentations, and few books. Half of the week, I grouped my materials into test subject categories. I have arranged the test subjects according to degree of difficulty for me. I allocated one full week and a half for Psychiatric Nursing alone. That was how I believed I was weak in this area. The third week, I tackled Community Health Nursing and Fundamentals of Nursing.  The fourth week was for Medical-Surgical Nursing and Maternal and Child Health. The fifth and last week, I retook all tests i have taken.

I made and printed answer sheets. Every day I practice answering a test with a timer. I checked my answers and learn from my mistakes. I downloaded practice tests from those generous individuals who share their materials online. I answered compilations of past board exam questions sold by review centers. Those were what I used. The answer keys provide rationale. There were entries though, which appear unbelievable. So I consult the books on those instances. I stood by the books’ explanations. I did not allow  my mind to wander away from what the books said. I heard many failures in board exams are due to over-analysis. That the board  exam is book-based, I should not make up stories and own reasoning.

I woke up at six in the morning, bathe, in comfortable clothes, cook and eat simple but nutritious meal, and begin the review. Mealtimes were break times for me when I turned on the television to obtain updates of contemporary issues. Then I turned off the TV and continue the afternoon review. I took short nap of 30 minutes at 3 or 4  in the afternoon, more to stretch my body on the bed for better circulation. Then dinner time is another break and short TV. I only spent about 30 to 45 minutes on mealtime. Then the evening review continued. It was a must that I sleep by 11 in the evening. In all of these daily routine, I never forget to open and close the day in prayer. This came with a song and scripture reading. I spent about 15 minutes on prayer.

While in CDO for the final coaching, I stayed with my ninang’s family. The daily schedule was from 8am to 5pm. In the evenings, I did not anymore do any review. I just spend time chatting with the people around. I look at my online mails and read online nursing related stories. After the 5-day final coaching, I had a week’s break and went back to my family. That week, I just browsed notes from final coaching. I have started to cool myself down, to relax my mind and let everything sink in. I have done my part, everything else was up to God’s plans for me. That was what I’ve set my heart and mind.

NLE passer.jpgAnd, God rewarded all my efforts! I passed the board exam! Though I’ve every reason to fail based on circumstances, yes. But, I did all that it takes to pass! I have not left any table unturned, no notes untouched. Most of all, I never doubted myself, not a bit. I knew that i would pass the exams based on how I’ve managed to finish the course in such complex situation.

Why I remember all these?

Because, another major exam is looming before me. A Goliath I have to slay, by God’s grace. In July, I will be taking a Comprehensive Exam for a doctorate degree. A doctorate in the field of Sociology, my first original field of study. The board exam experience gives me a good backdrop for my preparations for the compre exam. I now know what I need to do. I need two weeks of secluded review. No distractions. My family, with my three children bigger now, age 10-12-14 years old and my sister, we all were able to come up with the appropriate set-up for me. Again, I need to do my part, and God will do the rest.

In Jesus’ name.

Building the City of Golden Friendship: The Growth of Cagayan De Oro’s Zones Based on the Model of Burgess*

Authored by: Mary Ann Faller Daclan, Mindanao State University at Marawi, PH; Lilian C de la Peña, Capitol University, Cagayan de Oro City, PH; Ordem K Maglente, Caraga State University, PH; Mary Anne M Polestina, Mindanao State University at Buug, Zamboanga Sibugay, PH

Introduction

                                                         “The larger, the more densely populated, and the                                                                               more heterogeneous a community, the more                                                                                    accentuated the characteristics associated                                                                                        with urbanism will be.” – Louis Wirth

This paper explores the landscape of Cagayan de Oro, a highly urbanized city in northern Mindanao, southern Philippines. Exploration is based largely on interview with key informants and the use of secondary materials. Landscape change is examined in this paper to provide an initial perspective into deeper insights of the urbanization process that enveloped the city’s social context and unique character. The urbanization perspective forwarded by Burgess (in Park et al1925) is employed in this paper.

According to Burgess (1925) the typical processes of city expansion is best illustrated by a series of concentric circles, in which the area is differentiated through five successive zones, namely,

Zone I            – central business district

Zone II           – area of transition

Zone III          – worker’s place

Zone IV           – residential area of high-class apartment buildings or of                                                             exclusive “restricted” districts of single family dwellings

Zone V            – commuters’ zone

Burgess contends that cities do not just expand but,  rather, extend radially from the epicenter of economic activity. As extension takes place, the inner zone has the tendency to extend its area by invading the next outer zone. Thus, the physical expansion of an urban area, such as the city, is a consequence of its initial population expansion.

The process of urbanization is examined with the following objectives:

1) To determine the population of Cagayan de Oro City for the intercensal period of 1960, 1970, 1980, 1990, 2000, and 2010.

2) To illustrate the pattern of physical expansion of Cagayan de Oro City.

3) To describe the zones of Cagayan de Oro City which are created out of its own physical and population expansion.

The physical and demographic changes over time for Cagayan de Oro are examined in order to provide a deeper discussion on the evolution and the consequent social issues created out of its own unique development. Thus, the following hypotheses will be tested:

Hypothesis

Ho1: Increase in population results in the physical expansion of the city and the addition of zones.

Ho2: Population expansion is influenced by the development of the city’s commerce and business.

Conceptual Framework

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Significance of the Study

            The findings of the study would benefit sociologists and other scholars in the field of social sciences. It may contribute to understanding of the effects of urbanization and the consequences of in-migration at the macro level. It will help policy makers, particularly the local government units, in identifying areas where urbanization mechanisms may contribute positively to the development of the city.

Limitations of the Study

            The study is limited only to the urban barangays of Cagayan de Oro City. For the quantitative part, there is heavy reliance on the availability of data from government institutions (city local government and the Philippine Statistics Authority). The non-uniformity of the census years for all involved variables render to the non-computation of statistical relationships.  There is no survey conducted for lack of time. This is, however, sufficed with the exhaustive in-depth interviews with reliable key informants. Observations have been done in numerous occasions, having been roaming around the city for years.

Operational Definition of Terms

            The following are terms used throughout the paper. In understanding the discussion and arguments forwarded by the authors, these terms require definition.

            Business ventures. This refers to manufacturing, whole and retail trade, micro-finance institutions, financial cooperatives, general merchandise, entrepreneurial pursuits that earn income, government taxes, and required to apply for business permits.

            In-migration. This refers to the number of internal migrants moving to an area of destination (or from an area of origin) (Poston 2006).  In this research, in-migration pertains to the number of people settling in the city of Cagayan de Oro using data from intercensal period of 1960, 1970, 1980, 1990, 2000, and 2010.

            Physical Expansion. The natural adaptations to new types of social organization and analyzed through the theory of concentric zones (Burgess 1925). In this research, this refers to the visible and observable progression the city of Cagayan de Oro takes as it gradually widens from its smallest and simplest physical set-up into what it is at present, as retold by key informants.

             Population Expansion. This refers to the increase in the number of people residing in the city of Cagayan de Oro, as manifested in the data from intercensal period of 1960, 1970, 1980, 1990, 2000, and 2010.

            Zones.  These refer to concentric circles with areas, according to Burgess (1925 in Park et al., 1925) differentiated through five successive zones. The Zone I is the central business district, the Zone II is the area of transition, the Zone III is the worker’s place, the Zone IV is the residential area of high-class apartment buildings or of exclusive “restricted” districts of single family dwellings and, finally, the Zone V is the commuters’ zone.  In this research, the zones refer to the particular areas in Cagayan de Oro City where Park et al identified five zones are located, created out of its own physical expansion.

Methodology

            This section presents and discusses the research design, study site, method of data collection, instrument, ethical considerations, and analysis plan.

            Research Design

            This study used the descriptive design. It primarily described Cagayan de Oro City’s geographic and demographic characteristics. The description part is a scientific observation that is careful and deliberate. Hence, scientific descriptions, typically, are more accurate and precise than are the casual ones (Babbie 2014). Description of geographic characteristics focused on the city’s physical expansion. Demographic description encompassed the city’s population expansion as described through government records.

            Study Site

            The city is a first-class, highly-urbanized city, and the capital of Misamis Oriental. Previously, or until 1932, Cagayan de Oro is the capital of Misamis Province, comprised of Misamis Oriental and Misamis Occidental. Dubbed as Mindanao’s gateway, Cagayan de Oro has a land area of 488.9 sq. kms. and a population of 602,088 in 2010; and a population density of 1,500/sq.km (see Fig 2). About 44 per cent of the household population classify themselves as ethnically mixed people, 22.15 per cent Cebuano, 4.38 per cent Boholano, and 28.07 as other ethnic groups, according to the 2000 census of the NSO. A large portion or 87 per cent of the city’s residents are Roman Catholic. But the number of Protestants has increased in number in recent years. About 20 Protestant churches have nestled in the city. Cebuano is the primary language spoken in the city.

            The city was founded in 1871 and proclaimed a charter city in June 15, 1950. The city serves as the regional and economic center of Region 10; and list as one of the ten most progressive and competitive cities in the Philippines. It is also the tenth most populous city in the country. The city has 57 urban barangays and 23 rural barangays.

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            Cagayan de Oro is the melting pot of Mindanao because of its accessibility and business growth. Its economy is largely based on industry, commerce, trade, service and tourism. Investment in the city for the first six months of 2012 reached 7.4 billion pesos outpacing the local government unit’s expectation to nearly 100 per cent. Investments in the city are dominated by malls, high-rise hotels, condominiums, and convention centers. The net income of the city is pegged at 2,041,036,807.89 billion pesos.

            Methods of Data Collection

            A combination of qualitative and quantitative techniques was used for data gathering. For qualitative aspect, interviews and observation were used. For the quantitative part, data mining was used to obtain pertinent information from secondary sources.

            Key Informant Interview

            Interview with key informants was employed but in different time periods. Actual interview by all authors with a key informant for this study was made with one individual, an anthropologist conducting research on the history and social anthropology of the city. The interview was conducted in the informant’s office in Corrales Avenue, Cagayan de Oro on May 5, 2017 (for the interview guide, see Appendix A). Previous interviews made by one of the authors, de la Peña, on January 5, 2014 with two long-time residents of Balulang and Puntod are included in the paper. The data gained from these interviews provide valuable information on the development of these communities.

            Non-Participatory Observation

            The authors also made separate observations of Cagayan de Oro’s communities. De la Peña observed the barangays of Puntod and Balulang: Daclan on the barangays of Carmen and Bulua; Polestina on the barangays of Lapasan and Lumbia; and Maglente on the barangays of Cugman and Gusa.

            Data Mining

            Secondary materials and sources informed the discussion. The works of Madigan (1985), Ulack and others (1985), and Ulack (1978) on Cagayan de Oro are very helpful in understanding the spatial development and change of the city.

            The maps used in this paper were derived out of the Geographic Information System. They were taken from various sources, particularly Xavier University Engineering Resource Center (XU-ERC) and the City Planning and Development Office (CPDO) of Cagayan de Oro. These maps were used to examine the spatial variations with regards to the physical expansion of the City over the years.

            Explorations on demographic changes is largely based on secondary materials from various city and regional offices, namely, the City Planning and Development Office and the regional office of the Philippine Statistical Authority.

            Instruments

            For the qualitative aspect, the researchers framed guides for the interviews and observation. A question guide for the key informants was used to obtain information corresponding to the objectives of the study (Appendix A). An observation guide was used to provide focus to the researchers during the conduct of observation. That the researchers may not waste time what to look for; instead, they immediately spot on the objects they need to observe and record.

            Ethical Considerations

            Imperative in the conduct of this research is the observance of research ethics, from the conceptualization to the report-writing stage and all the more during the data collection.  An oral consent was obtained from the key informants prior to the conduct of the interviews. The key informants were duly informed of the study’s objectives and assured of confidentiality (e.g., no names to be mentioned in the report or in any medium such as paper presentation, and no taking of picture).  Prior to the start of the in-depth interviews, an expressed consent was obtained from the key informants.

            Analysis Plan

            For the qualitative part, specific responses to the questions in the recorded interviews were encoded, sorted, and categorized according to objectives of the study.  The data were integrated in the presentation of the results of the study.

            For the quantitative part, the data culled were encoded in Microsoft Excel for computations of intercensal change and graphing purposes. The unit of analysis is the city of Cagayan de Oro focusing on the physical and population expansions through the use of census in years 1960, 1970, 1980, 1990, 2000 and 2010.  Five-year surveys’ trend is established and depicted in graphic forms.

Formula Used

            Intercensal Increase shows the percent increase in a demographic element (like population count) within a ten-year period. It is obtained by subtracting the percent population in present year (for instance 2010) with the percent population in past year (for instance 2000) divided by percent population of past year (2000) multiplied by one hundred to have the percentage.

intercensal increase formula.jpg

            Intercensal analysis is used for the city’s data on population involving census years 1960to 2010. Hence, calculation of five intercensal percent change was done. For clearer presentation, graphs are made based on the raw data from secondary sources, particularly the Philippine Statistics Authority census.

            Lieberson’s Index of Population Diversity is where S is the sum of squares of the proportion of the community’s population affiliated with each ethnic grouping. The result varies from 0.00 when all people come from one ethnic group, to a value very close to 1.00 when everyone is a stranger to everyone else.

            Calculation is easier when all elements for a variable (mother tongue or ethnic affiliation) are all placed on the first column. The frequency counts for each element are placed on the corresponding second column. On the third column are the P values, which are individually obtained for each element by dividing each frequency with the total frequency. On the fourth column should be the square of P (P2). The total of squared P values is the S. Formula: LIPD = 1.00 – S.

Results

            This section presents the results of the study following the research objectives of this paper.

1) Population Expansion of Cagayan de Oro

            Based on available data from the Philippines Statistics Authority (formerly National Statistics Office), the city of Cagayan de Oro has increment population from 1960 to 2010 (Figure 3). As previously mentioned, Cagayan de Oro became a city in June 15, 1950.  But it took her 1,660 years to raise its first 1,000 settlers (CDOC PDO).  To continue the presentation of CDOC PDO, it was only after 205 years when some 9,000 people were added. And this means that in 1873 the city, then known as Cagay-an, had its first 10,000 people.

            Actual Population: 1960 – 2010

            Cagayan de Oro has a consistent and continuous increase of five-decade (1960 to 2010) actual population counts of the city (see Fig 3).  The figures for these periods are consistent to the population situation of the whole country. Census data for 1960 suggest that Cagayan de Oro had contributed about one-third of one per cent (.30%) to the country’s total population of 27 million. With each passing decade, as Cagayan de Oro’s population increased in thousands, the country’s population increased in millions. Hence, by 2010, Cagayan de Oro contributed .65% to the Philippines’ population of 92 million. This is a tiny fraction of the country’s total population, but a considerable double figure increase for the city since 1960.

cdo actual pop 1970 - 2010.jpg

            Intercensal change to Actual Population: 1960 – 2010

            Highest intercensal population is evident during the periods of 1960 and 1980 (see Fig 4). The highest upsurge of the city’s population occurred from 1960 to 1970, an all-time high of 83.31%. This was followed by still high percent increase of 77% in the next decade (1970-1980).  This explosive growth of population may be a consequence of synergistic effects of combined high fertility, low mortality, and dynamic migration.  There may have been increased gap between births and deaths.  It may be worthwhile to note that the decade 1970 to 1980 was characterized by socio-political turmoil in the whole country due to martial law. It may have affected the movements of people from chaotic and unstable neighboring communities prompting in-migration to a promising Cagayan de Oro City.

cdo actual pop 1970 - 2010 Intercensal Change.jpg

            Though there appears to be a continuous increase in the city’s population in the successive decades, the increase appears to taper into about less than half in comparison to the increase in the earlier periods. On the whole, the city’s five-period intercensal increase in its population was higher than the Philippines’ figures (in red). It seems that in this part of the country, population soared higher during these particular decades.

            New Residents: 1995 – 2005

            There may be dearth of data to explain the upsurge of population in Cagayan de Oro City from 1960 to 1990. But, in the succeeding years, there appears to be a demographic variable found to be at play in the city’s population intercensal increase.  In the following decades, particularly 2000 and 2010, census data reveal data on the specific question “where were you five years ago?” Figure 4.1 shows the number of residents in Cagayan de Oro City who admitted that they just became residents of the city in 1995 and 2005. These in-migrants totaled to 24, 376 in 1995 and 33,334 in 2005.

            Of the migration data (Figure 4.1), it appears that there were more women than men who in-migrated to, and became residents of, the city from 1995 to 2005. Predominance of women in-migrants to the city continued through these years. A scenario exemplified over half intercensal increase of men and women migrants in 2005 from ten years before (in 1995). Men migrants constituted 50.65% intercensal increase to the population. Women migrants were recorded at 56.71%.

cdo HH pop not reidents 5yrs ago by sex 2000 and 2010.jpg

            Barangay Population: 1990 – 2000

            With in-migration to the city that brought about an increase to the population, new residents add up to the existing population at the barangay level.  In which barangays these new residents prefer to live is where they consider beneficial to them factoring in their daily budget for transportation towards their jobs and at the same time saves them time in commuting. Figure 4.2 depicts the population of selected urban barangays of Cagayan de Oro City in 1990 and 2000 census. These are the urban barangays with 800 and over population count.

CDO brangays pop 1980 to 2000 with arrows.jpg

            As depicted by the line graph (Fig 4.2), the 13 urban barangays with over 800 actual population counts can be grouped into two categories when it comes to population change. The two categories nearly have equal proportions of barangays. The areas that have decreasing population are Barangays 15, 32, 31, 25, 23, and 10. And, those that show increasing population are Barangays 26, 13, 17, 22, 18, 27, and 24. When plotted on the Cagayan de Oro City’s map, what is noticeable is the proximal distance of these highly populated barangays (of over 800 actual population count) to each other, all situated within the core of the city. In Figure 4.2.1, Barangay 18 is located between Magsaysay Street and Capistrano Street, Del Pilar Street, and the Marcos Bridge area. Evident also is the decreasing population of barangays close to Barangay 1 or the city center where the city hall is located. In contrast, population has been increasing for barangays where business and commerce expanded in the 1990s, specifically Corrales Extension and Recto Avenue.

CDO map3.jpg

            Figure 4.3 depicts the intercensal change of the highly populated barangays in Cagayan de Oro City. It is Barangay 24 that has the highest intercensal change, with almost two hundred per cent (184%) population increase from 1990 to 2000. Situated at the city’s core, this barangay is at the crossroads of Sergio Osmeña and Claro M. Recto streets, which leads to Limketkai Drive. Beyond this is the location of two of the earlier big malls in the city – Limketkai Mall and Gaisano City. Next to these malls, this decade saw the establishment of two gigantic malls – Centrio Ayala in 2012 and SM Downtown Primier in 2017.  Barangay 24 may have barely a thousand population count until 2010, however, should its intercensal per cent change continues in the next decade, it is highly probable that by 2020, this barangay’s population may double up.

cdo-occupied-housing-units-intercensal-change1.jpg

            Barangay 32 has decreased intercensal percent change of -.40%. This area is mostly occupied by business establishment, near Oro Rama Department Store. As what Dr Sealza (2017) mentioned, there may be many people seen in the area on a daily basis, but these people are there only for business transactions. By nighttime, these people have already gone back to their residences, in another barangays.

            Occupied Housing Units in Barangays

            There are ten barangays in Cagayan de Oro City with over 300 occupied housing units by 2010 (Fig 5). Barangay 26 has the most increase of occupied housing units since 1990 (along Recto Avenue).There were only 366 housing units in 1990 that leaped to 542 in 2000. Barangay 13 also had only 221 occupied housing units in 1990, but shoot up to 492 by 2000. Barangay 18 had 463 occupied housing units in 2000 from its 254 in 1990. These data on occupied housing support the data on increased population count in the same barangays for the same census year 2000 (Fig 4.2).

            While these barangays had increased occupied housing units, Barangays 25 and 32 had decreased occupied housing units in the same year.  These are consistent with the data on decreased population count in the same barangays for the same census year 2000 (Fig 4.2). This appears to be a good indication that the number of people in these barangays has corresponding houses to stay.  The other barangays, though there is a leaning for increase or decrease, only manifested slight change.

cdo occupied housing units Intercensal Change.jpg

            With over a hundred per cent (123%) change, Barangay 13 has the highest intercensal change in occupied housing units. This is followed by Barangay 18 with 82% intercensal change. These two barangays both have increased population in 2000 (Fig 4.2).  These barangays also are near to each other, in the northwestern part of Cagayan de Oro City, just at the edge of the core part of the city, where zone 2 also starts. Noticeable is Barangay 15 which has almost no change in its occupied housing units in ten-year period.

            There is over a quarter (-27%) intercensal decrease on the occupied housing units of Barangay 25. This is followed by Barangay 32 with -23% intercensal decrease. These two barangays are opposite each other. Barangay 25 is at the northern part of the core city while Barangay 32 is at the southern part.

CDO brangays pop intercensal change 1980 to 2000.jpg

            Lieberson’s Index of Population Diversity

            For census 2000, there are forty-two (42) different mother tongue listed (Box 1).  Following the formula learned from class (Urban Sociology), the result of the calculated proportion is 0.9024, which gives a Lieberson’s result of 0.0976.

Lieberson's Index of PD CDo 1990 box1a

2) Physical Expansion of Cagayan de Oro

            Expansion of Built Areas, 1950s-2000s

            The physical expansion of Cagayan de Oro is captured in Landsat images for the period of 1953, 1973, 1992, 2002, and 2006 (Sabines and Guanzon 2007). The Landsat images below clearly present the growth of the city’s built area, particularly concrete roads, houses, and other structures as captured through satellite imaging (see Fig 6). Likewise, based on the same images it can readily be noticed that built areas were initially developed along the banks of Cagayan de Oro River as evidenced by the 1953 satellite image. Two decades later, the same trend can be noticed as the built area expanded along the river banks and close to the seashore of Macajalar Bay. Nineteen years later, expansion continued with the creation of more built areas along the river bank and Macajalar Bay. Starting in 2002, specifically, built areas increased and were added to the upper sections of the city, notably Upper Carmer and Lumbia. The same goes with regard to expansion of areas along the other side of the Cagayan de Oro river.

            The physical expansion of Cagayan de Oro as presented by the images taken for several periods is affirmed by one informant. A key informant who has studied the history of the city and who has also conducted archaeological excavations of its first settlement, the Huluga, described the expansion of Cagayan de Oro.

            Transferring the Settlement Downstream

            The first settlement named Huluga is located on the upper portion of the city, where the barangays of Lumbia, Taguanao, and the old CDO airport, are all located. This is believed to be the first settlement prior the arrival of three Recollect friars from Caraga. The Huluga site was excavated by the National Museum in 1970 and unearthed were human bones, pottery shreds, and other household implements, such as obsidian knife, that clearly reveal a settlement before the country’s Spanish period. The Archaeology department of the University of the Philippines, however, believes that Huluga is merely a temporary shed for the early inhabitants on their way downstream of the river to trade products. The clear information coming out of these perspectives is the presence of the early inhabitants in the site.

expansion maps.jpg

            The Recollect friars, it is said, came from Butuan and visited Huluga in order to convince Datu Salangsang, the leader of the settlement, to be converted from his animist practice to Catholicism. It did not take long for the friars to get Salangsang into their religion. The conversion was facilitated by the military skill of one friar who trained Salangsang and his men how to defend themselves from the Moro raiders of Kabungsuwan. Part of imparting military skill to Salangsang’s men is the fortification of the settlement.

            In order to fortify settlement safe from the raiders, it was transferred to the lower section, today the Gaston Park. Salangsang’s men with the help of the military-friar were able to fend off the Moro raiders, and from then on never returned to Huluga. The defeat of the Moto raiders is the reason why the settlement is first called Kagayhang or the place of shame for the Muslims.

            The Start of Development

            It did not take long for the new settlement to prosper beside the river. There could be inter-island trade, possibly facilitated by the huge river that comes across the city.  Archaeological artifacts on display at the Museo de Oro at Xavier University reveal the presence of Chinese and Vietnamese porcelain jars and powder cases.

            Beside the settlement was established the Catholic church, now the San Agustin Cathedral, the office of the alcalde mayor, and the plaza. The plaza complex, so popular among Spanish-established towns in the Philippines, also guided the initial development of the city. The area became also the residence of migrants coming from the Visayas and Luzon – and these were traders such as the Roa family and the educated town administrators, such as the Corrales and Velez families.  It was also during this time that the name Kagayhang was changed to Cagayan de Misamis, capital of Misamis Province until 1932. Later on, when it became a charter city in 1950, Oro was added to mean gold, as this mineral was panned out of the river before. Moreover, almost all places in the country with big rivers are named Cagayan, such as Cagayan in the north.

            The initial commercial area of Cagayan is Casa Real, present day Burgos. Casa Real was demolished in 1910 to give way to the town hall. Commerce transferred to what is now Divisoria from Burgos. Later on, Burgos became a residential area. While the old character of Burgos can still be felt today its current state is one of houses very near each other and most in dilapidated condition.

            Beside Divisoria or at the other end of Calle Real is the town market where the amphitheatre can also be found. The predecessor of this town market could be beside the river where the first settlement was. The town market was transferred to Cogon in the mid 1980s or during the time of Mayor Justiniano “Tinying” Borja whose family owned areas there. Borja donated part of his land for the market to be transferred in 1958 to Cogon. As the place name suggests, the area before the market’s transfer is filled with cogon grass. With the transfer of the market to Cogon, the amphitheatre was also demolished.

            Xavier University, a boy’s school at first, was first established by the Jesuits beside the plaza, or beside the girl’s school Lourdes College. But the Jesuits later transferred their school to its present location beside Divisoria for lack of space for expansion in the former location. Corrales Avenue, the present location of Xavier has so much land to offer before the Second World War. The area could not have been ideal for residence and business because it had a cemetery there before owned by the PIC or by the Aglipayan Church. Houses sprouted more along Corrales later in time with the evacuation there of residents from Camiguin Island following the eruption of Hibok-hibok in 1953. The development of Divisoria as an area for commerce also created other residential settlements, particularly Macasandig.

            During the time of Mayor Tirso Neri, whose family owned the land in Divisoria, the area was always burnt down to ashes. The good mayor decided to donate his family’s land, and built the center aisle to prevent fire from spreading to both sides of the street. Tirso Neri comes from the Spanish Neri of Cagayan de Oro and of different descent from the Muslim Neri who used to own a large part of the city. The Muslim Neri are relatives to the families of Rivera, Pelaez, Marfori, and Chavez.

            The area of present-day Lim ket Kai Mall, Capitol University, and Centrio Mall during this time had very few houses. The area also was inundated every high tide or when it rained hard. There were very few houses on this area until the establishment of some business outfits, which the biggest is Coca Cola Bottling Company. Houses there before stood on stilts, similar to the few residences in Barangays Puntod and Macabalan. It was also in the 1950s the port of Cagayan de Oro was established. The establishment of the port attracted more residents, particularly the laborers of paper mills that sprouted in Puntod-Macabalan together with the port.

CDO map zones.jpg

            It is interesting to look into the establishment of major commercial outfits currently present in Cagayan de Oro (Table 1). This validates the expansion of business and, likewise, the expansion of residential areas in a radial manner.

CDo establishments.jpg

            The case of Balulang

            Upper Carmen, specifically Masterson Avenue, where one can now find Xavier Heights, SM Shoemart, and other posh subdivisions such as Xavier Heights, Pueblo came later when the Jesuits bought the grazing lands owned by the families of  Chavez, Avancena, and Roa (based on interview with one pioneering family in Balulang by de la Peña, date of interview January 19, 2014 ). There were caretakers and some few settlers up to Balulang. These pioneering settlers cultivated coconut and earned from its copra as by-product. A certain member of the Roa family built a merchandise store on what is now the center of Balulang. In this store, the enterprising Roa engaged in retail with the settlers – by buying their copra and in turn exchanged it with household stuff. At this time, Balulang was filled with trees and coconuts and the cows raised by the settlers for the three wealthy families. Nowadays, the land of Balulang is filled with residential houses inside gated subdivisions, mostly for professionals. There is also a significant population of Muslim residents in the area and a mosque is established.

            When these lands were bought by the Jesuits in the 1980s where they established their College of Agriculture, SEARSOLIN and the Xavier Science Foundation, development followed them there. The area is now becoming a residential area for middle class families. The settlers were provided residential lands inside Xavier Heights Subdivisions but only after heated engagement and negotiation.

            After the 1990s real estate development also developed to cater to the demands of the informal settlers. It is interesting to note that first generation migrants who came as laborers gave way to educated children – the second generation settlers, who demanded for better communities.   Middle class housing was made available to them in areas such as Upper Carmen, at the outskirts of the city such as Opol.

            The case of Puntod

            Puntod is a barangay located at the rim of Cagayan de Oro River and Macajalar Bay. It is an offshoot of the population expansion of nearby Macabalan. The pioneering families, particularly Beja and Dacer, of Puntod came from Macabalan. Puntod is part of the 1980s NHA project RCDP with the World Bank. Many residents of Puntod are Bol-anon and Cebuano who came in as labourers of the many factories that sprouted within the area for the period of 1950s-1960s (interview with one pioneering family member of Puntod by de la Peña, dated 2014 March 5). In the 1970s, most sections of Puntod are with water, especially during high tide. Houses there were on stilts. These watery areas were reclaimed later on, and which gave way to concrete houses. Presently, only a tiny portion of Puntod have houses on stilts.

            The warehouses are still present in Puntod but, generally, it is a residential area for first generation settlers and pink-collar workers from rural areas who seek room for rent in the area. The renting out scheme could have also been facilitated by social networks. Homeowners and renters may have come from the same areas in the neighboring rural provinces.

            Informal settlers

            The case of Cagayan de Oro’s informal settlers is an interesting discussion to look into in-migration. These urban informal settlers came to the city for social opportunities but they initially start out their residence as squatters. There were informal settlers all over the area of Puntod-Macabalan because of the port and the opportunity to earn from its daily activities. The National Housing Authority (NHA) and the city government, with loan coming from the World Bank, engaged in the RCDP a project that started in 1984 to establish communities of people and to distribute lands to settlers. These were mostly migrants to the city who came in to partake of the economic opportunities. The same arrangement was made for the informal settlers of upper Carmen.

            The work of Ulack (1978) reveals that the oldest respondents have lived in the city as early as 1949. The Recto Avenue squatter settlement is the oldest in the city.

            The Coca Cola Bottling Company found on the Recto Avenue attracted settlement for the squatters. Other more established squatter areas as found in Macabalan, the Piaping Puti and Piaping Itum. Macabalan is where the container port is found. The other recently opened squatter area during Ulack’s interview is Lapaz beside the proposed, at that time, Agora market. Out of the 241 respondents of Ulack from three established squatter areas of Cagayan de Oro in the late 1970s, the highest number of them says they are engaged in labor jobs. The table below shows the labor number employed by the CDO port. It is most likely that this labor force have found settlement in the nearby squatter areas.

CDO unskilled labor force.jpg

            The expansion of business pursuits in the city was mentioned, albeit anecdotal, b the key informants and the secondary materials. During most part of the Spanish Period or until the American Period commerce was only engaged in the Calle Real, or the present day Burgos Street, beside the political center of the city. The business area expanded to include the watery sections of the city in the 1960s.

            The data on the city’s business and commerce are mostly recent and, therefore, the significant change per decade cannot be clearly gleaned. Currently, there are 22 industrial establishments, foreign and local, listed in the inventory prepared by the City Planning and Development Office. These industrial establishments are in the categories of agriculture, pharmaceutical, and electronics. While the data are recent, it is still evident that business is booming in the city as seen on the revenue data gained from manufacturing establishments.

CDO Business data - from Lilian 1.jpg

            This growth is seen also on the increasing number of banks and financial institutions (see Fig 5). From the categories indicated in the graph below only two types of financial institutions are dwindling, namely, the finance cooperatives and rural banks. Upsurge is evident on the number of pawnshops, micro finance institutions, and finance cooperatives.

Fig 7.1 Number of Banks and Financial Institutions.jpg

            The above data are corroborated by the increasing number of business permits issued from the year 2006 to 2010 (Fig 8). Greatest increase within this period is seen for 2009-2010. In the succeeding period of 2011-2015, the same trend of increasing number of approved permits can be seen from the data.

List of Business Permits Issued by Type Cagayan de Oro City

Fig 8 List of Business Permits Issued by Type Cagayan de Oro City 2006 to 2010.jpg

Fig 8.1 Number of Business Registrations Cagayan de Oro City 2011 - 2015.jpg

            The highest number of business permits issued by the city is under the business category of wholesale and retail trade, followed by community, social and personal services. In the latter category, it is evident that entrepreneurial pursuits are significantly carried out in the city. Mining and quarrying have the lowest number.

 Discussion

            The history of Cagayan de Oro, including the recent past, points out to development and progress. The “city of golden friendship” which Cagayan de Oro is known for, together with another popular description “the gateway to Mindanao” projects an image of economic growth and prosperity. Indeed, in its regional context, Cagayan de Oro appears to be the most modern, that is gauged by its number of shopping malls and entertainment, in relation to another urbanized city, Iligan and other cities, such as, Ozamis, Tangub, El Salvador, Malaybalay, and Valencia. This seeming progress, however, is hosted by numerous factors, both spatial and temporal, that contribute to what the city is now.

            In this paper, the landscape of Cagayan de Oro is examined using various data on population and physical expansion. Both sets of data are important in analyzing the unique character of the city. Burgess’s model of city expansion is used. The data gathered for this paper reveal similarities to what Burgess found out in the West.

            Based on the historical account of Madigan (1995) the city of Cagayan de Oro started out a settlement along the riverbank of the Cagayan River. This settlement is a resettlement site, actually, of a community of Higaunon who inhabit Macahambus Cave, located on the upper Western portion of the city. Constant raid from the Moro and advice from a Recollect to move downstream to better protect themselves from piratical attacks moved the community to relocate. The first settlement downstream is beside the current location of Gaston Park and the Saint Augustine Cathedral.

            Spanish colonization changed the landscape into a plaza complex, and herein followed the establishment of sections categorized into commercial, political, residential for the upper class and another residential area for the lower class. From then on, the population of Cagayan de Oro has been increasing together with progress in business and commerce. The labor requirement of a city that is dependent on the service sector has resulted in the increase of population, most probably in-migrants from neighboring areas. However, the Lieberson Index of Population Diversity for Cagayan de Oro’s 2000 census data on ethnicity reveals a result of 0.0976. The result is lower than 1.0 and nearer to 0, and which indicates that Cagayan de Oro’s population is less diverse. This is congruent to the analysis of Costello and others (1982) of major cities in the country. Costello and others analyze a less ethnic diverse population because of the unique cultural migration trait of the Filipinos to migrate as a family, or to have a chain of migration coming from the same areas. It is common, for instance, to have communities in urban areas named “Little Bohol,” Little Cebu,” or “New Bohol” signifying the dominance of these ethnic groups in particular areas.

            The phenomenon of less ethnic diversity, however, in urban areas such as Cagayan de Oro does not downplay the increase in its population. Based on census data, the city has increment population from 1960 to 2010. Before this period, population increase was staggered and slow, but there was increase nevertheless. However, intercensal population is evident during the periods of 1960 and 1980. The highest upsurge of the city’s population occurred from 1960 to 1970, an all-time high of 83.31%. This was followed by still high percent increase of 77% in the next decade (1970-1980). The population of women has grown more than men during the same period. These data appear to be in consonance to what Todaro explained about predominance of women migrants from rural to urban areas. And, a bigger fraction of these women migrants to the urban areas usually join the informal sector (Todaro and Smith 2012), having lower competitiveness in terms of education and skills required for by the formal sector. Despite lesser opportunities that await in-migrants from rural areas in the city, men and women, nevertheless, opt to be in the city for better wages in comparison to what their area of origin could offer. There is also the presence of recreation areas in the city that rural areas lack, which pose attraction that beckons young men and women of adventurous nature.

            Business appears to grow also during the period of 1960-1980. The data gathered from several sources on the year of establishment of major business outfits in Cagayan de Oro reveal the building of major shopping malls during the same time, particularly Oro Rama in 1969, as well as the container port in Macabalan in 1971, the multinational company Nestle in Tablon in 1983. These major business outfits did not only contribute to the increase of revenue but also to the entry of laborers. The number of unskilled laborers for the container port within the decade of 1970-1980 reveals highest number in the initial years of the 1970s. The entry of laborers also required the expansion of built areas to give way to residential structures, may it be on middle class residential areas of slums and squatters.

            The lands at images over the years (Sabines and Guanzon 2007) present succinctly the growth of built areas in Cagayan de Oro. Specifically, the growth reveals expansion in a radial manner as observed by Burgess in the West. Interviews with a key informant from Balulang reveal the growth of this community from real estate development. What used to be a timberland and grazed by the cows of three prominent families is now a hub for middle class housing units. The development of Puntod is a little different. While conversion took the form of reclamation, Puntod took in labourers from the paper milling factories and other factories that opened there together with the development and enlargement of the container port in 1971. The population within Puntod-Macabalan area significantly increased during this time that a World Bank project in the 1980s was initiated to formally house the laborers and in-migrants.

            Ulack (1975) examined the biggest squatter areas in the city and found out their close proximity to major business outfits. Particularly, the squatter area along Recto Avenue in Barangay 22 grew to house the laborers of the Coca Cola Bottling Company located on the same street. Recent data gathered on the business and trade of the city reveals continuous growth. The population is still growing but the highest intercensal increase is seen for the period of 1960-1970. This period also saw the growth of squatter areas in the city as revealed by Ulack.

            The outward physical expansion of Cagayan de Oro is evident with the establishment of residential areas on the outskirts of the city. The upper section of Balulang and Lumbia are now filled with subdivisions, and so are areas on the other side if the city, particularly Iponan. These are commuter’s zone or the fifth zone in Burgess model. It would take a commuter almost one hour to reach this zone coming from the loop or the first zone following the same model of Burgess. The middle zones are occupied with business districts and squatter areas intermeshed in a web of economic relations. The nature of business in this zone is changing. Coca Cola Bottling started out at the heart of the city but now has transferred to Villanueva. What remains of the business zone now are shopping malls and groceries, shops, and hotels and restaurants.

            The residential areas beside the first zone of the Loop have given way to these commercial outfits. Barangays closest to the city center where the city hall is located all have decreasing number of population and housing units, as revealed by census data. It is evident that these areas have been fully converted to business and commerce and with a decreased number of night-time population.

            Based on the data gathered and consequent analysis made, the two hypotheses forwarded in this paper hold ground. Indeed, population increase is evident on the census together with the establishment of significant and large scale business and commerce in the city. Both phenomena results in the physical expansion of the city, specifically a radial expansion outward. The tidal zone along Puntod-Macabalan has been reclaimed to give way to housing units and the timberland of Balulang and Lumbia, as well, for middle class subdivisions. The same is true for the agricultural lands of Iponan which is similarly filled with housing units. These housing units were built for the labour force that fuels Cagayan de Oro’s modernization and urbanization.

References

Babbie, Earl.  2001.  The Practice of Social Research, 9thed.  California, USA: Wadsworth/ Thompson Learning.

Burgess, Ernest W. 1925. “The Growth of the City: An Introduction to a Research Project.” Pp 47-62 in The City, edited by M. Janowitz. USA: The University of Chicago Press.

Costello, Michael A, Federico V Magdalena, and Isaias S Sealza. 1982. “Community Modernization, In-migration and Ethnic Diversification: The Philippines, 1970-1975.” Philippine Sociological Review 30:3-14.

Lieberson, Stanley. 1969. “Measuring Population Diversity.” American Sociological Review, 34: 850-862.

Madigan SJ, Francis. 1995. The Early History of Cagayan de Oro. The Local Historical Sources of Northern Mindanao, edited by FR Detmetrio, SJ, pp.1-38. Cagayan de Oro City, Xavier University.

Philippine, Republic of the. Various census and data sets. Philippine Statistics Authority Census Compilation.

Poston, Dudley L. 2006.Migration. In Turner, Bryan S. (ed) The Cambridge Dictionary of Sociology. New York, USA: Cambridge University Press.

Sabines, Mark Alexis and Yvette B Guanzon. 2007.  A look at Cagayan de Oro: Past, Present, and Future. Southeast Asian-German Summer School on Urbanization.Powerpoint material accessed at www.forum_urban_futures.net on 24 November 2014.

Todaro, Michael P and Stephen C Smith. 2012. Urbanization and Rural-Urban Migration: Theory and Policy. Economic Development, 11th ed. USA: Addison-Wesley.

Ulack, Richard. 1978. “Role of Urban Squatter Settlements.” Annals of the Association of American Geographers, 68(4):535-550.

Ulack. Richard, MA Costello, M Palabica – Costello. 1985. “Circulation in the Philippines” Geographical Review 75(4): 439-450.

Wirth, Louis. 1938. Urbanism as a Way of Life. The American Journal of Sociology 44(1):1-24.

Appendix A. Interview Guide for Key Informant

Interviewers introduce themselves

Introduce the objectives of the interview

Present ethical consideration followed

Secure permission of the respondent

  1. Do you have a favorite story of Cagayan de Oro?
  2. How is this story related to the development of the city?
  3. Can you tell us about the initial settlements of the city?
  4. When was the first settlement established?
  5. Who are the pioneering families?
  6. Are these families still here in the city?
  7. When did the city start to grow economically?
  8. What is the direction of its growth?
  9. Did this economic development attract in-migrants?
  10. Presently, the city has a huge population what could be the most significant factor of this development?
  11. What are the social problems developed out if this growth?

Interviewers thanking the respondent.

Appendix A. Checklist for Observation

Zone I

  • Business establishments
  • Government offices
  • Parks
  • Churches
  • Tall buildings
  • High density

Zone II

  • Deteriorated housing
  • Abandoned buildings
  • Slums

Zone III

  • Boarding houses
  • Warehouses
  • Single houses tenements

Zone IV

  • Single family homes
  • Garages /yards
  • Warehouses
  • Garden

Zone V

  • Large houses
  • Large gardens
  • Open spaces
  • Less density
  • Car parks

*This piece of work is a research output from collaborative efforts of  teammates Mary Ann  F Daclan, Lilian C de la Peña, Ordem K Maglente and Mary Anne M Polestina in Urban Sociology course (Summer 2017, PhD Program, XU-ADCU, CDO under Dr. IS Sealza) 

Economic and Population Growth: Their Association with Total Carbon Emissions

The Costs of Many 

Economic and Population Growth: Their Association with Total Carbon Emissions

Author: Mary Ann F Daclan, Mindanao State University at Marawi, PH

Introduction

“The earth will not continue to offer its harvest, except with faithful stewardship. We cannot say we love the land and then take steps to destroy it for use by future generations.” 

― Pope John Paul II

Carbon emission has become a worldwide concern tagged along the phenomenon of climate change. The latter has turned into a byword as concepts El Niño, La Niña and the like came afloat when experiential devastations beset countless people in various parts of the world. For the Intergovernmental Panel on Climate Change (2007), climate change refers to any change in climate over time, whether due to natural variability or as a result of human activity.

The Population Reference Bureau (2007) reported that in the environment, “carbon dioxide emissions have grown dramatically in the past century because of human activity. These emissions are a key contributor to climate change that is expected to produce rising temperatures, lead to more extreme weather patterns, facilitate the spread of infectious diseases, and put more stress on the environment.”

Intergovernmental Panel on Climate Change (2014) highlighted that carbon emissions have increased since the pre-industrial era, driven largely by economic and population growth. This has led to atmospheric concentrations of carbon dioxide, methane and nitrous oxide that are unprecedented in at least the last 800,000 years (IPCC 2014). Their effects, together with those of other anthropogenic drivers, have been detected throughout the climate system and are extremely likely to have been the dominant cause of the observed warming since the mid-20th century (IPCC 2014). Total anthropogenic GHG emissions have continued to increase over 1970 to 2010 with larger absolute increases between 2000 and 2010, despite a growing number of climate change mitigation policies (IPCC 2014).

There are both natural and human sources of carbon dioxide emissions. Natural sources include decomposition, ocean release and respiration. Human sources come from activities like cement production, deforestation as well as the burning of fossil fuels like coal, oil and natural gas (WYI 2016). Continuous rise of carbon emission to the atmosphere threatens the world’s stability primarily affecting all life forms: human beings, plants and animals.

Objectives

This paper intends to find out whether the extent of carbon emissions is associated with population and economic growths. Specifically, it seeks to address the following:

  1. To describe the economic growth of different countries.
  2. To describe population growth of the different countries.
  3. To determine the level of carbon emissions in different countries.
  4. To assess possible significant association of economic and population growths with level of carbon emissions.
  5. To test the difference between three-grouped of economic and population growth on total carbon emissions.
  6. To know the possibility of attaining zero carbon emission.

 

Hypotheses

The following hypotheses tested were:

Ho1: There is no association between economic growth and level of carbon emissions.

Ho2: There is no association between population growth and level of carbon emissions.

Ho3: There is no difference between three-grouped of economic growth on total carbon emissions.

Ho4: There is no difference between three-grouped of population growth on total carbon emissions.

Significance of the Study

The world is beset with countless challenges that have to be confronted head on by particular countries most affected with or unanimously by alliances of countries concerned. These challenges are in a mixture of chronic societal ills in universal scope and magnitude since time immemorial and contemporary problems that just surfaced about a decade or two. Carbon emissions belong to the latter, for although these have been in existence a long time (as per World Bank records) they have not troubled the world as they recently do. They just surfaced along with the contemporary problem called climate change.

Countries of the world forged alliances, like the Paris Treaty, to particularly address climate change that includes carbon emissions.  This particular study comes timely as knowledge about carbon emissions as may be associated with population and economic growths may render better understanding about this social phenomenon.

Limitations of the Study

The study includes only 187 out of 210 countries for lack of data on gross national income for year 2013 of thirty-three countries, and on carbon emissions of twelve countries. Moreover, countries with less than one million metric ton total carbon emissions were not included. Hence, the results of the computations can only describe the 187 countries.

The paper focused only on year 2013 based on the latest available data on carbon emissions. The other two variables – population and economic growths – may have 2016 data, but for consistency purposes with carbon emissions, only the 2013 data are used.

Definition of Terms

The following terms, which pose technicalities, are hereby defined for easy reference in the foregoing discussions:

Carbon Dioxide Emissions (CO2). These are the total values from burning oil, coal and gas for energy use, burning wood and waste materials, and from industrial processes such as cement production. The carbon dioxide emissions of a country are only an indicator of one greenhouse gas that affects the Earth’s radiative balance. It is the reference gas against which other greenhouse gases are measured, thus having a Global Warming Potential of 1. CO2 are measured in metric tons per capita (PRB 2016; WB 2017). The data for this variable were culled out from the 2016 Population Data Sheet that featured the 2013 GNI (PRB 2016).

Gross National Income (GNI). This is used to measure the economic growth of a country. It refers to per capita based on purchasing power parity (PPP). PPP GNI is gross national income (GNI) converted to international dollars using purchasing power parity rates (WB 2017). An international dollar has the same purchasing power over GNI as a U.S. dollar has in the United States. GNI is the sum of value added by all resident producers plus any product taxes (less subsidies) not included in the valuation of output plus net receipts of primary income (compensation of employees and property income) from abroad. Data are in current international dollars (WB 2017). The data for this variable were culled out from the 2014 Population Data Sheet that featured the 2013 GNI (PRB 2013).

Population Growth. This refers to the estimated population count of the countries included in the study in Population Data Sheet for year 2013 (PRB 2013). The data for this variable were culled out from the 2013 Population Data Sheet that featured the 2013 population count (PRB 2013). Data on population count are measured in millions.

Methodology

This section describes the research design, locale inclusion for the analysis, methods of data collection, and statistical tools used with the corresponding formulas and procedures used in the calculations of the economic and population growth with total carbon emissions.

Research Design

This paper used the descriptive-comparative design. It describes significant demographic attributes such as population and economic growths and carbon emissions among countries classified as least developed (low-income), less developed (lower and upper middle-income) and more developed (high-income).

Locale

For lack of data on carbon emissions at the local level in the Philippines, including the Mindanao regions, this paper levelled up to involve countries classified by World Bank as least developed, less developed, and more developed. These categories were specifically differentiated using gross national income: low-income, lower middle-income, upper middle-income, and high-income (Table 1).

carbon emissions fig1

There are 187 out of 211 countries with corresponding data on carbon emissions in 2013, gross national income for economic growth, and population count for population growth variables included in this exercise.

Categorization of Countries

The Population Reference Bureau (2016) Data Sheet lists all geopolitical entities with populations of 150,000 or more and all members of the UN. These include sovereign states, dependencies, overseas departments, and some territories whose status or boundaries may be undetermined or in dispute. More developed regions, following the UN classification, comprise all of Europe and North America, plus Australia, Japan, and New Zealand. All other regions and countries are classified as less developed. The least developed countries consist of 48 countries with especially low incomes, high economic vulnerability, and poor human development indicators; 34 of these countries are in sub-Saharan Africa, 13 in Asia, and one in the Caribbean (Appendix A).

Sub-Saharan Africa includes all countries of Africa except the northern African countries of Algeria, Egypt, Libya, Morocco, Sudan, Tunisia, and Western Sahara. World and regional totals pertain to regional population totals that are independently rounded and include small countries or areas not shown. Regional and world rates and percentages are weighted averages of countries for which data are available. Regional averages are shown when data or estimates are available for at least three-quarters of the region’s population.

Countries Included

The final list of countries included those with complete available data for the three variables, and which carbon emissions’ data does not fall below 1 million metric tons. The countries that lacked were removed from the rows for encoding. Hence, from 210 countries, only 187 are included.

carbon emissions fig2

 

Methods of Data Collection

This paper primarily used data mining to obtain data on carbon emission, gross national income and population growth from World Bank and Population Reference Bureau’s 2013, 2014 and 2016 Population Data Sheets. The latest available data (year 2013) for carbon emission is in 2016 Population Data Sheet. To have a uniform data for the same year 2013, the population count used is from 2013 Population Data Sheet. While the gross national income data come from 2014 Population Data Sheet. Hence, all three variables are for year 2013.

The data culled from the Population Reference Bureau were copied and encoded in the spreadsheets of Microsoft Excel version 2010. This allowed manageable editing and sorting while in SPSS software, each variable was specifically defined in the variable view mode. When the data were already sorted according to countries, they were copied and pasted on the data view of the SPSS version 17 software. Using the class notes, the steps were followed in the computations using various statistical tools.

Statistical Tools Used for Analysis

The data culled were encoded in Microsoft Excel to weed out those that have no entries. Final entries were copied and pasted on the data view of statistical software SPSS version 17. Class notes on the procedures were used as guide in the computations.

The unit of analysis for this paper is country for which three variables are particularly focused, namely: economic growth, population growth, and carbon emissions. Based on the continuous and categorical data, the statistical tools applied in computations include: frequency and percentages; measures of central tendencies, particularly mean and median and Pearson correlations. The strength of correlation value is based on this guide (Class Notes 2016). The categorical data come from the recodes in SPSS of the continuous variables, for the purposes of having more extensive data analysis of the variables involved.

One-Way Analysis of Variance (ANOVA). This was done on the three-grouped independent variables economic and population growth as factors against the dependent variable total carbon emissions. If a significant difference among the grouped income and population would result, a posthoc (a posteriori) test would be done using the Tukey test to determine which among the three groups has the most contribution on total carbon emissions. SPSS would put a asterisk ( * ) on the significant differences and would show which group was significantly different to the other two groups (Garth 2008).

The procedure included choosing the following options while in SPSS: Analyze, Compare means, One-way ANOVA, Enter dependent variables on Dependent List Box, Enter independent variable on Factor List, Options: set confidence interval at 95%, Continue, and Ok. And to proceed to pot-hoc test, choose post-hoc, Tukey, set Significance level AT 0.05, and ok.

Correlation. The primary purpose of correlation analysis here is to measure the strength of relationship between the independent variables, economic growth and population growth, with the dependent variable, carbon emissions. The coefficient of linear correlation, r, is the measure of the strength of linear relationship between pairings of these included variables. This strength of relationship is determined by the amount of effect any change in one variable has on the other (Babbie 2001).

The linear correlation coefficient, r, will always have a value somewhere between -1 and +1.  Positive (+1) is the measure of perfect positive correlation while negative (-1) is the measure of perfect negative correlation. Correlation will be considered high when it is close to +1 or close to -1 and low when it is close to zero.

carbon emissions fig3

 

Dataset Used. The dataset used for the statistical computations is:

[DataSet1] d:\ANNfiles\Ann_SI\PhD\FS2016 Soc461 Data Mgt & Processing in Soc Research ALOVERA\data for final exercise carbon emissions.sav

Frequency and Percentage Distribution. These were used to describe the categorical data from grouped values of population counts, gross national incomes, and total carbon emissions.

Median. This is a measure of central tendency, the middle number when pieces of data are ranked in order according to size.

carbon emissions fig4

Recoding. To transform continuous variables into categorical, recoding was done using SPSS. The gross national income was recoded into three groups: countries with less than $1,035 GNI per capita are classified as low-income countries, those with between $1,036 and $4,085 as lower middle income countries, those with between $4,086 and $12,615 as upper middle income countries, and those with incomes of more than $12,615 as high-income countries (UN 2014). GNI per capita in dollar terms is estimated using the World Bank Atlas method.

Standard Deviation.  It is a measure of the unpredictability of a random variable, expressed as the average deviation of a set of data from its mean and computed as the positive square root of the variance. It is considered the most useful and important measure of dispersion which has all the essential properties of the variance plus the advantage of being determined in the same units as those of the original data. In this study is centered on finding out the relationship between two variable, it is simply mean to include this statistical tool in the analysis of data.

The standard of deviation of a population is:

Ƿ = sqrt{ ƿ2} = sqrt {∑ ( Xi – µ)2 /N }

Where,

Ƿ = population standard deviation

Ƿ2 = population variance

µ = population mean

Xi = ith element from the population

N = number of the elements in the population.

 

Weighted Mean. This is a measure of central tendency.  This was used to describe the centrality of responses of the respondents on the continuous data for population counts, gross national incomes, and total carbon emissions. The expected value is denoted by using one of the following equations:

Formula:

Population mean = µ = ∑X / N   OR    Sample mean = x = ∑x / n

Where,

∑X = sum of all the population observations,

N = number of population observations,

Procedure in the Ranking of the weighted mean include: (1) To rank in terms of weighted mean, place 1st rank to the highest weighted mean, then 2nd rank to the next highest weighted mean and so on. (2) In case of a tie, get the average corresponds to their rank. For example, the two observations tie at 2nd and 3rd rank, so their average rank is: 2 + 3 / 2 = 2.5. Thus, the two observations have an equal rank of 2.5th.

Discussion

This section presents and discusses the findings of the paper in accordance to the objectives of this exercise: differential economic growth among countries; population growth; the level of total carbon emissions; associations of economic and population growths with level of carbon emissions; and, the possibility to attain zero carbon emission.

Differential Economic Growth

The United Nations (2014) Data Sheet lists all geopolitical entities with populations of 150,000 or more and all members of the UN. These include sovereign states, dependencies, overseas departments, and some territories whose status or boundaries may be undetermined or in dispute. More developed regions, with high income, following the UN classification (Appendix A), comprise all of Europe and North America, plus Australia, Japan, and New Zealand.

Other regions and countries classified as less developed in relation to more developed countries are comprised of upper and lower middle income countries. The least developed countries consist of 48 countries with especially low incomes, high economic vulnerability, and poor human development indicators; 34 of these countries are in sub-Saharan Africa, 13 in Asia, and one in the Caribbean. Sub-Saharan Africa includes all countries of Africa except the northern African countries of Algeria, Egypt, Libya, Morocco, Sudan, Tunisia, and Western Sahara (PRB 2016).

carbon emissions fig5

By United Nations’ income specification, the 187 countries included in this exercise are dominated by high-income (83) countries with over 12,615 gross national income. This is followed by the upper middle-income (56) countries, which the Philippines belong, having 7,820 gross national income in 2013 (Table 1). The Philippines need to almost double such gross national income to level up to the high-income category.

The income classification’s advantages over the older “three worlds” system revolve around the focus on economic development and the depiction of the relative economic development of various countries that does not group together all less developed nations into a single “Third World” (Macionis 2012). There is also specific differentiation of middle income countries into upper and lower income, giving due consideration to the wide range of the middle income from 1,036 to 12,615. This is an objective and forthright classification based on an easily measurable variable.

Countries where Industrial Revolution first took place more than two centuries ago have gone extremely farther ahead in economic arena compared to the fledgling ones. Formidable years have seen these countries with productivity increase more than a hundredfold. The power of industrial and computer technology makes a small centuries-old country as economically productive as a whole continent (Macionis 2012). The culture lag in countries still largely in agricultural setting renders them at the poor extreme of the income spectrum.

Table 2. The Countries’ Gross National Income Per Capita, 2013 (US Dollars)
Minimum Maximum Mean Median Std. Deviation
GNI 2013 600 123,860 17,261 10,850 19,537
N 125

Table 2 shows the wide economic gap between countries. The minimum gross national income of poorer countries (600) is more than a thousand-fold to that of richer countries (123,860). A huge amount (SD = 19,537) separates a country’s gross national income from the mean (x=17,261). The average gross national income tends to be higher owing to the few countries with extremely higher amounts. The median income (10,850) of these 187 countries fell farther from the mean, lower by over six thousand dollars. This means that half of the countries (93 to 94) have gross national income below 10,850.

The six countries at the bottom of the chronology of gross national income, below a thousand dollars, are from Africa: Central African Republic, Democratic Republic of Congo, Malawi, Liberia, Burundi, and Niger (Appendix A). While high-income countries are dominated by American and European countries, the topmost two countries with over a hundred dollars gross national income are from Asia: Macao and Qatar (Appendix A).

 

Differential Population Growth

Figure 3 depicts the distribution of population in different countries in 2013. While the graph for gross national income (Figure 2) has higher columns to the right side, indicating higher incomes, the graph below (Figure 3) has lower column to the right side. However, it is not what it seems, for the value of the few countries (18 of 187) is high (as high as billions) the cumulative total population is a whooping billions-fold bigger (Table 3). The larger group with (82 of 187) countries that have lesser number of people (less than 5 million) have a meager cumulative population of only 130 million.

Geographically small countries have the smallest population count. Tuvalu has only 10,000 population followed by Palau with 20 thousand and San Marino with 30 thousand. Tuvalu is located in the Pacific Ocean, north east of Australia (CIA World Factbook 2017). Palau is an archipelago of over 500 islands, part of the Micronesia region in the western Pacific Ocean. And, San Marino, also known as the Most Serene Republic of San Marino, claim to be the oldest surviving sovereign state in the world (CIA World Factbook 2017).

The ten most populous countries of the world are Japan, Russia, Bangladesh, Nigeria, Pakistan, Brazil, Indonesia, United States, India, and China (PRB 2013). Consistently, the topmost two countries with over one billion people are in Asia – India and China. The over 96 million population placed Philippines at rank 12th amongst all countries.

carbon emissions fig6

 

carbon emissions fig9g.jpg

 

There is a wide gap between populous and less populated countries with a standard deviation of over 140 million from the mean of over 37 million (Table 4). The pull of populous countries on their extremely sparsely populated counterparts separates the mean from the median by about 30 million. The minimum number of people is in the 10-thousand populated Tuvalu while the maximum number of people can be found in 1.3 billion populated China. Despite China’s one-child policy for over 40 years already, because of its huge land area, it remained to be highly populated.

carbon emissions fig9h.jpg

 

Differential Level of Total Carbon Emissions

     Amid the world’s hullaballoo about climate change and how mitigation should be done through reduction of total carbon emissions by countries under the Paris Treaty, are the very few countries (16 of 187) with over a hundred million metric tons of total carbon emissions (Figure 3). These are only 16 countries, but their contribution to total carbon emissions is tremendously a high 2 billion (Table 5). While the 115 countries with less than 10 million total carbon emissions have only given off a total carbon emissions of 230 million (Table 5). Not even three percent (2.4%) of what the 16 countries have emitted.

The same could be said of the 56 countries with considerably moderate contributions of 10 to 100 million metric tons of total carbon emissions (Figure 3). Their contributions to total carbon emissions are even less than a quarter (21.9%) of what the 16 countries have emitted. The Philippines is one of these moderately contributing countries with 26.8 million metric tons of total carbon emissions. The Philippines is side by side with Nigeria, Kuwait and Czech Republic having similar range of total carbon emissions at 26 million metric tons (Appendix B).

carbon emissions fig7.jpg

 

The high-emitting countries have contributed three-fourths (75.6%) of the total carbon emissions. The top two countries with very high carbon emissions are the United States with 1.4 billion and China with 3 billion total carbon emissions (Appendix B).

carbon emissions fig9c.jpg

Countries with barely 50 thousand total carbon emissions are Kiribati, Marshall Islands, Vanuatu, Sao Tome and Principe, Dominica, Federated States of Micronesia, and Comoros (Appendix B). The minimum total carbon emissions of 17 thousand only (Table 6) is from Kiribati, an independent republic located in the central Pacific Ocean, about 4,000 km (about 2,500 mi) southwest of Hawaii (Kurain 2007). The Marshall Islands, with only 28 thousand total carbon emissions, are a sprawling chain of volcanic islands and coral atolls in the central Pacific Ocean, between Hawaii and the Philippines (Kurain 2007).

 

carbon emissions fig9i.jpg

There is a wide gap among countries’ total level of carbon emissions. The high-emission countries pull up the values and render the average at 50.6 million metric tons, about 46 million away from the median, which is only 3.7 million. Hence, countries are far apart from the mean by 235 thousand (Table 6).

Association between Economic and Population Growth

with Level of Carbon Emissions

This section presents and analyses computed data using correlation to address the fourth objective.

Table 7 shows the results of correlations of the variables economic and population growth with total carbon emissions. Literature suggests (IPCC 2014) that total carbon emissions are brought about by population and economic growth. However, in this particular study, there appears to be no association between economic growth, through gross national income, and total carbon emissions (r = .070, n = 187 p = .343) for year 2013 data.

When examined thoroughly, the listing (Appendix B) shows inconsistency of countries with high gross national income and high total carbon emissions. Not one of the topmost nine countries with highest gross national income is included as highest in total carbon emissions.  It is possible that the high-income countries do not correspondingly contribute high total carbon emissions for their sophisticated measures at mitigation. For instance, being on top in total carbon emissions among the Southeast Asian countries in the 1980s to 1990s, Singapore’s carbon emissions have considerably decreased in 2000 onwards; possibly may be the effects of Singapore’s implementing mitigation measures in the country’s key sectors (NCCS 2016).

carbon emissions fig9b.jpg

It is totally a different story for population and total carbon emissions as there appears to be a high and positive association between the countries’ population and total carbon emissions (r = .799, n = 187 p = .000) for year 2013 data. This may entail that as population may increase, total carbon emissions may also rise. It could be that when there are more people, there is possibility for more extractions from the environment, like overconsumption of trees, may increase carbon emission. Increased population may entail expansion that requires more resources extracted from the environment.

Difference between Grouped Economic and Population Growth

on Level of Total Carbon Emissions

This section presents and analyses results of computed data of the grouped independent variables against the dependent variable total carbon emissions.

The results on Table 8 shows no significant difference among grouped countries’ gross national income to total carbon emissions (F (3,183) = .709, p = .548). This is consistent with the correlation results above. It may be that when there’s no association between the tested variables, there may also be no difference. It may be that whatever is the income state of countries, whether low-income or high-income, each has somehow contributed to the total carbon emissions. The high-income countries may also have crafted mitigation policies to reduce total carbon emissions amid highly technological processes that increase income, as in the case of Singapore (NCCS 2016).

carbon emissions fig9a.jpg

The results on Table 9 shows significant difference among grouped countries’ population to total carbon emissions (F (2,184) = 22.726, p = .000). Notably, this result somehow support the positive correlation of population and total carbon emissions in correlated variables.

carbon emissions fig9.jpg

There is a significant difference (0.000) among the three groups of countries’ populations. So it is appropriate to proceed to a posthoc (a posteriori) test, using the Tukey test to find out which of the three groups has the most contribution to total carbon emissions. The results show that the group of countries with over 75 million population 3 was significantly different to the other two groups of lower population counts.

carbon emissions fig8.jpg

Possibility to Attain Zero Carbon Emission

In 2008, four countries Iceland, New Zealand, Norway and Costa Rica were competing to be the first of the world’s 195 nations to go entirely carbon neutral (Lean and Ray 2008). The four countries formally signed up to go zero carbon, joining the Climate Neutral Network launched at the annual meeting of the Governing Council of the United Nations Environment Programme.

The Goal to Attain Carbon Neutral

All the main contenders get much of their energy from renewable sources. Iceland has gone the furthest, already achieving almost complete carbon neutrality in heating buildings and in electricity generation using geothermal energy that heats much of the rest of the country (Lean and Ray 2008).

New Zealand aimed to generate 90 per cent of its energy from renewable sources by 2025, and to halve its transport emissions per head by 2040. But the country has a particular problem with agriculture, which accounts for half its emissions of greenhouse gases.

Norway has set an even more ambitious target, aiming for carbon neutrality by 2030, despite being the world’s third largest oil exporter. It already gets 95 per cent of its electricity from hydroelectric power, and heavily taxes cars and fuel: a 4×4 costs four times as much as in the United States (Lean and Ray 2008).

Costa Rica plans to reach its goal by 2021. It has just released a plan of action, which relies heavily on planting trees to soak up emissions. Last year it planted five million of them, a world record, and the banana industry – the country’s largest exporter – has promised to go carbon neutral. However, its number of cars has increased more than five-fold in the past 20 years and its air traffic more than seven-fold in just six, making its task far harder (Lean and Ray 2008).

The Dark Horse in Attaining Zero Carbon  

The only country in the world to make such a switch and now as of 2016 is the world’s first country to become carbon negative is Bhutan (Protano-Goodwin 2016), a country often overlooked by the international community (Mellino 2016). This small nation lies deep within the Himalayas between China and India, two of the most populated countries in the world. But the country of about 750,000 people has set some impressive environmental benchmarks (Mellino 2016).

Bhutan’s massive tree cover, 72% of the country is still forested, which made it a carbon sink. Being a carbon sink means that Bhutan absorbs over 6 million tons of carbon annually while only producing 1.5 million tons.

How did Bhutan become carbon negative? It is noteworthy that Bhutan has long based their political decisions on a Gross National Happiness (GNH) index, abandoning economic growth as their compass (Mellino 2016). Environment as a central component in human happiness catapulted environmental protection as top priority in Bhutan’s political agenda. A promise made back in 2009 to remain carbon neutral in the days ahead picked up speed from there. Bhutan banned export logging, amended the constitution to include that forested areas would not drop below 60%, and utilized free hydroelectric power generated by many rivers over environmentally devastating fossil fuels.

carbon emissions fig9dOther creative environmental initiatives include a partnership with Nissan to provide the country with electrical cars (Protano-Goodwin 2016). The government has also started providing rural farmers with free electricity in order to lessen their dependence on wood stoves for cooking. More trees have been planted by volunteers who set a world record by planting 49,672 trees in just an hour’s time. To celebrate the birth of the first child of the royalty, all 82,000 households in Bhutan planted a tree, while volunteers planted another 26,000 in various districts around the country, for a total of 108,000 trees. Bhutan is aiming for zero net greenhouse gas emissions, zero-waste by 2030 and to grow 100 percent organic food by 2020.

 

Conclusions

From the data presented earlier, it was shown that there is differential economic growth among countries. There is a wide economic gap with the minimum gross national income of poorer countries at 600 dollars is more than a thousand-fold to that of richer countries at over 120 dollars. Many countries have gross national incomes extremely distant from the mean income due to extremely high income of few countries. The median income even differs from the mean by over six thousand dollars.

There is differential population growth with few countries in billions of cumulative population count compared to numerous countries with lesser than 5 million people in meager cumulative population of only 130 million. There is a wide gap between populous and less populated countries with a standard deviation of over 140 million from the mean of over 37 million.

There is differential level of total carbon emissions among countries. It takes only 16 high-emitting countries to have total carbon emissions of 2 billion metric tons while 115 low-emitting countries have only given off total carbon emissions of 230 million. Not even three percent of what the 16 countries have emitted. The 16 high-emitting countries have contributed three-fourths (75.6%) of the total carbon emissions.

Associations favor population growth and total carbon emissions, but not economic growth and level of total carbon emissions. There appears to be a high and positive association between the countries’ population and total carbon emissions for year 2013 data. This may entail that as population may increase, total carbon emissions may also rise. It could be that when there are more people, there is possibility for more extractions from the environment, like overconsumption of trees, may increase carbon emission. Hence, there is enough evidence of a failure to reject null hypothesis Ho1 there is indeed no association between economic growth and level of carbon emissions. However, there is enough evidence to reject null hypothesis Ho2 as there appears to be an association between population growth and level of carbon emissions.

While there is no shown difference between gross national income and total carbon emissions, one-way ANOVA results showed significant difference between three-grouped countries’ population and total carbon emissions. Hence, there is enough evidence of a failure to reject null hypothesis Ho3 as there is indeed no significant difference between economic growth and level of carbon emissions. However, there is enough evidence to reject null hypothesis Ho4 as there appears to be a significant difference between population growth and level of carbon emissions, with grouped countries of over 75 million population having more contribution to total carbon emissions than those with lesser population.

Finally, there is possibility to attain zero carbon emission with what Bhutan has already achieved. People of Bhutan have actively and seriously follow measures the country specified to hit their goal at zero carbon emissions. The possibility of attaining zero carbon emission is not just an impossible ambition for Bhutan, the first country in the world to be. Bhutan stopped destroying their environment and started protecting it, something every country and individual has the power to do. For a country that has already gained the world’s respect and attention. By 2030 Bhutan plans to reach zero net greenhouse gas admission and to produce zero waste by increasing its share on renewable energy sources such as wind and biogas, among others.

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PIA. 2016. Retrieved 10 January 2017 from Philippine Information Agency website: http://news.pia.gov.ph/article/view/8614791 14418/prd-s-nod-to-paris-climate-change-agreement-earns-praises-from-youth-sector#sthash.KtTX1CUo.dpuf

PRB. 2013. 2013 World Population Data Sheet. Washington DC USA: Population Reference Bureau.

PRB. 2014. 2014 World Population Data Sheet. Washington DC USA: Population Reference Bureau.

PRB. 2016. 2016 World Population Data Sheet: With a Special Focus on Human Needs and Sustainable Resources. Washington DC USA: Population Reference Bureau.

Protano-Goodwin, Tyler. August 2016. Bhutan Becomes the World’s First Carbon Negative Country. Retrieved 10 January 2017 from Global Vision International Website: http://www.gvi.co.uk/blog/bhutan-carbon-negative-country-world/ UK: GVI.

PSA. 2016. Philippine Statistics Authority. Retrieved on 7 October 2016 http://nap.psa.gov.ph/activestats/psgc/SUMWEBPROV-JUNE2016-CODED-HUC-FINAL.pdf

Student.com. 2008. What are Pearson’s r and scatterplots? Retrieved on 10 January 2017 from: http://statistics-help-for-students.com/How_do_I_report_Pearsons_r_and_scatterplots_in_APA_style.htm#.WCcJYvl97IU

United Nations. 2016. About LDCs. Retrieved on 10 October 2016 from: http://unohrlls.org/about-ldcs/

WYI. 2016. Main sources of carbon dioxide emissions. Retrieved 10 January 2017 from What’s Your Impact website: http://whatsyourimpact .org/greenhouse-gases/carbon-dioxide-emissions

APPENDIX A

carbon emissions fig9e.jpg

APPENDIX B

 

carbon emissions fig9f.jpg

 

+this was submitted as a required exercise in Data Management and Processing in Social Research, SS2016-17

Provinces According to Regions in the Philippines as of December 2016

As of 31 December 2016, there are 81 provinces in 18 regions

NIR – Negros Island Region Code: 180000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
NEGROS OCCIDENTAL 184500000 19 Mun 13 Cities 662 Bgys 1st 1,575,159 2,396,039 796,521
NEGROS ORIENTAL 184600000 19 Mun. 6 Cities 557 Bgys) 1st 679,583 1,286,666 538,553
CAR – Cordillera Administrative Region Code: 140000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
MOUNTAIN PROVINCE 144400000 10 Mun. 144 Bgys 4th 90,497 154,187 215,738
IFUGAO 142700000 11 Mun. 175 Bgys 3rd 98,462 191,078 262,821
BENGUET 141100000 13 Mun. 1 City 269 Bgys 2nd 183,608 403,944 282,659
ABRA 140100000 27 Mun. 303 Bgys 3rd 147,615 234,733 416,525
APAYAO 148100000 7 Mun. 133 Bgys 3rd 60,281 112,636 441,335
KALINGA 143200000 7 Mun. 1 City 152 Bgys 3rd 115,280 201,613 323,125
REGION I (Ilocos Region) Code: 010000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
LA UNION 13300000 19 Mun. 1 City 576 Bgys 1st 410,659 741,906 149,770
ILOCOS NORTE 12800000 21 Mun. 2 Cities 557 Bgys 1st 338,135 568,017 346,789
ILOCOS SUR 12900000 32 mun. 2 Cities 768 Bgys 1st 373,070 658,587 259,600
PANGASINAN 15500000 44 Mun. 4 Cities 1,364 Bgys 1st 1,505,181 2,779,862 545,101
REGION II (Cagayan Valley) Code: 020000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
NUEVA VIZCAYA 25000000 15 Mun. 275 Bgys 2nd 234,638 421,355 397,567
CAGAYAN 21500000 28 Mun. 1 City 820 Bgys 1st 568,628 1,124,773 929,575
ISABELA 23100000 35 Mun. 2 Cities 1,055 Bgys 1st 829,963 1,489,645 1,241,493
QUIRINO 25700000 6 mun. 132 Bgys 3rd 92,804 176,786 232,347
BATANES 20900000 6 Mun. 29 Bgys 5th 9,531 16,604 21,901
REGION III (Central Luzon) Code: 030000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
BATAAN 30800000 11 Mun. 1 City 237 Bgys 1st 414,890 687,482 137,298
ZAMBALES 37100000 13 Mun. 1 City 247 Bgys 2nd 289,460 534,443 383,083
TARLAC 36900000 17 Mun. 1 City 511 Bgys 1st 633,415 1,273,240 305,360
PAMPANGA 35400000 19 Mun. 3 Cities 538 Bgys 1st 1,057,339 2,014,019 206,247
BULACAN 31400000 21 Mun. 3 Cities 569 Bgys 1st 1,519,817 2,924,433 279,610
NUEVA ECIJA 34900000 27 Mun. 5 Cities 849 Bgys 1st 1,187,149 1,955,373 575,133
AURORA 37700000 8 Mun. 151 Bgys 3rd 111,211 201,233 314,732
REGION IV-A (CALABARZON) Code: 040000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
RIZAL 45800000 13 Mun. 1 City 188 Bgys 1st 1,129,374 2,484,840 119,194
CAVITE 42100000 17 Mun. 6 Cities 829 Bgys 1st 1,520,319 3,090,691 157,417
LAGUNA 43400000 25 Mun. 5 Cities 674 Bgys 1st 1,323,246 2,669,847 191,785
BATANGAS 41000000 31 Mun. 3 Cities 1078 Bgys 1st 1,248,059 2,377,395 311,975
QUEZON 45600000 39 Mun. 2 Cities 1,242 Bgys 1st 857,011 1,740,638 906,960
MIMAROPA Region Code: 170000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
OCCIDENTAL MINDORO 175100000 11 Mun. 162 Bgys 2nd 215,146 452,971 586,571
ORIENTAL MINDORO 175200000 14 Mun. 1 City 426 Bgys 1st 392,210 785,602 423,838
ROMBLON 175900000 17 Mun. 219 Bgys 3rd 161,643 283,930 153,345
PALAWAN 175300000 23 Mun. 1 City 433 Bgys 1st 364,175 771,667 1,703,075
MARINDUQUE 174000000 6 Mun. 218 Bgys 4th 121,381 227,828 95,258
REGION V (Bicol Region) Code: 050000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
CATANDUANES 52000000 11 Mun. 315 Bgys 3rd 140,467 246,300 149,216
CAMARINES NORTE 51600000 12 Mun. 282 Bgys 2nd 248,654 542,915 232,007
SORSOGON 56200000 14 Mun. 1 City 541 Bgys 2nd 375,567 740,743 211,901
ALBAY 50500000 15 Mun. 3 Cities 720 Bgys 1st 678,869 1,233,432 257,577
MASBATE 54100000 20 Mun. 1 City 550 Bgys 1st 436,957 834,650 415,178
CAMARINES SUR 51700000 35 Mun. 2 Cities 1063 Bgys 1st 893,813 1,822,371 549,703
REGION VI (Western Visayas) Code: 060000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
CAPIZ 61900000 16 Mun. 1 City 473 Bgys 1st 418,755 719,685 259,464
AKLAN 60400000 17 Mun. 327 Bgys 2nd 300,292 535,725 182,142
ANTIQUE 60600000 18 Mun. 590 Bgys 2nd 279,600 546,031 272,917
ILOILO 63000000 42 Mun. 2 Cities 1,901 Bgys 1st 1,003,077 1,805,576 507,917
GUIMARAS 67900000 5 Mun. 98 Bgys 4th 90,425 162,943 60,457
REGION VII (Central Visayas) Code: 070000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
CEBU 72200000 44 Mun. 9 Cities 1,203 Bgys 1st 1,434,809 2,619,362 534,200
BOHOL 71200000 47 Mun. 1 City 1109 Bgys 1st 690,532 1,255,128 482,095
SIQUIJOR 76100000 6 Mun. 134 Bgys 5th 57,523 91,066 33,749
REGION VIII (Eastern Visayas) Code: 080000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
SOUTHERN LEYTE 86400000 18 Mun. 1 City 500 Bgys 3rd 235,821 399,137 179,861
EASTERN SAMAR 82600000 22 Mun. 1 City 597 Bgys 2nd 251,859 428,877 466,047
NORTHERN SAMAR 84800000 24 Mun. 569 Bgys 2nd 316,769 589,013 369,293
SAMAR (WESTERN SAMAR) 86000000 24 Mun. 2 Cities 951 Bgys 1st 442,662 733,377 604,803
LEYTE 83700000 40 Mun. 3 Cities 1,641 Bgys 1st 895,173 1,567,984 651,505
BILIRAN 87800000 8 Mun. 132 Bgys 4th 92,830 161,760 53,601
REGION IX (Zamboanga Peninsula) Code: 090000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
ZAMBOANGA SIBUGAY 98300000 16 Mun. 389 Bgys 2nd 320,710 584,685 360,775
ZAMBOANGA DEL NORTE 97200000 25 Mun 2 Cities 691 Bgys 1st 546,771 957,997 730,100
ZAMBOANGA DEL SUR 97300000 26 Mun 1 City 681 Bgys 1st 541,233 959,685 591,416
REGION X (Northern Mindanao) Code: 100000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
MISAMIS OCCIDENTAL 104200000 14 Mun 3 Cities 490 Bgys 2nd 321,843 567,642 205,522
BUKIDNON 101300000 20 Mun. 2 Cities 464 Bgys 1st 658,697 1,299,192 1,049,859
LANAO DEL NORTE 103500000 22 Mun. 1 City 506 Bgys 2nd 344,950 607,917 415,994
MISAMIS ORIENTAL 104300000 23 Mun. 3 Cities 504 Bgy 1st 471,910 813,856 354,432
CAMIGUIN 101800000 5 Mun. 58 Bgys 5th 55,427 83,807 23,795
REGION XI (Davao Region) Code: 110000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
DAVAO ORIENTAL 112500000 10 Mun. 1 City 183 Bgys 1st 270,087 517,618 567,964
COMPOSTELA VALLEY 118200000 11 Mun. 237 Bgys 1st 344,143 687,195 447,977
DAVAO DEL SUR 112400000 14 Mun. 2 Cities 519 Bgys 1st 517,024 868,690 677,104
DAVAO OCCIDENTAL 118600000 5 Mun. 105 Bgys new province; no data available 0 0
DAVAO DEL NORTE 112300000 8 Mun. 3 Cities 223 Bgys 1st 505,464 945,764 342,697
REGION XII (Soccsksargen) Code: 120000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
SOUTH COTABATO 126300000 10 Mun. 2 Cities 225 Bgys 1st 411,246 827,200 442,881
SULTAN KUDARAT 126500000 11 Mun. 1 City 249 Bgys 1st 383,264 747,087 529,834
COTABATO (NORTH COTABATO) 124700000 17 Mun. 1 City 543 Bgys 1st 599,197 1,226,508 900,890
SARANGANI 128000000 7 Mun 141 Bgys 2nd 239,983 498,904 360,125
REGION XIII (Caraga) Code: 160000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
AGUSAN DEL NORTE 160200000 10 Mun. 2 Cities 253 Bgys 3rd 190,108 332,487 354,686
AGUSAN DEL SUR 160300000 13 Mun. 1 City 314 Bgys 1st 300,772 656,418 998,952
SURIGAO DEL SUR 166800000 17 Mun. 2 Cities 309 Bgys 1st 319,415 561,219 493,270
SURIGAO DEL NORTE 166700000 20 Mun. 1 City 335 Bgys 2nd 273,693 442,588 197,293
DINAGAT ISLANDS 168500000 7 Mun. 100 Bgys 68,856 126,803 103,634
ARMM – Autonomous Region in Muslim Mindanao Code: 150000000
Province Code Info Income Class Registered Voters Population Land Area
-2010 (as of May 1, 2010) (as of 2007, in hectares)
TAWI-TAWI 157000000 11 Mun. 203 Bgys 3rd 156,027 366,550 362,655
BASILAN 150700000 11 Mun. 1 City 210 Bgys 3rd 150,672 293,322 322,447
SULU 156600000 19 Mun. 410 Bgys 2nd 280,527 718,290 343,699
MAGUINDANAO 153800000 36 Mun. 506 Bgys 1st 470,021 944,718 972,904
LANAO DEL SUR 153600000 39 Mun. 1 City 1,159 Bgys 1st 459,012 933,260 1,349,437

Convergence of Cousins: How Common Language Brings About Cohesion

“Common language facilitates cohesion among cousins coming from diverse cultural milieu who converge for the first time in a span of 10 to 20 years.” – #emefdy

When our first child (of three children) was born in early 2003, she became the eldest among future maternal cousins but, the youngest among first-world based paternal cousins. Yes, all of her five paternal cousins live in the developed western part of the world. Three of the five were actually born in the city that never sleeps. The other two, after having emigrated from the Philippines when they were between 2 to 9 years old, grew up in their new country where the temperature is a usual negative 20.

From 2002 to 2006, in three successful pregnancies, our three children were born healthy and complete, all via C-section under the adept hands of Loladoki. Kim in early 2003, Johm in late 2004, and Sam in late 2006.

In one of the milk company sponsored pregnant conferences I attended in 2002, a speaker shared about how her child knows how to speak English, Thai, and Tagalog. They have lived in Thailand for few years and the kid’s babysitter was a young Thai woman who speaks to her child in Thai language. What I learned that time are truly beneficial to my children:

  • That the child’s capacity to learn and speak multiple languages is endless as long as there is no confusion
  • That the child’s mind will be confused if the languages are mixed in one sentence
  • That whenever you speak to a child ,  what ever is the language, speak in straight one language.
  • That you do not underestimate a child’s capacity to understand what you are saying because of language difference. Just speak.
  • That you do not underestimate a child’s ability to understand you because the child is still a child, still an infant. Just speak to the child, the infant

Back then, I was considering the paternal cousins of my eldest child and thought that I would like them to understand each other when they be in the same space. So I thought that since all of the five paternal cousins speak English, I would make my child speak English too to be able to converse with them.

Using my English learned from formal education , I did speak to my children regardless of their age. I started talking to them while still in utero as fetus. I talked about breastmilk as the best food they can have. I talked to them about the world, about my family, about anything I thought relevant to their coming out to the world soon. It was like orientation to what they will be into when they joined humanity.

During infancy, I played to them the CD with classical music given by a milk company. As toddlers, I let them watch  videos featuring  Barney and friends, Strawberry Shortcake, movies featuring animals like Ariel, Spirit,  Ice Age, Lion King, and the like. My mama came to help me babysit for few months. My mama does not speak English. I told her to just speak in Visayan language, my first language, the vernacular here in Mindanao. I specifically told my mama to speak in straight Visayan and not to mix even a single ENglish word to her sentence, like the usual I hear around, “eat na,” or “drink na ug water o,” “ali na kay mag sleep na ka.”

So, I guess, the technique went well with my kids. They normally speak English like it’s their first language. Actually, they started to speak Visayan when they went to kindergarten and socialized with their Visayan-speaking classmates.

In February of this year, 2017, my husband’s sisters came home to celebrate the 80th birthday of their mother, my mother-in-law. Each sister brought with her one son, both in early twenties. It’s the first time for my children, now 14, 12 and 10 years old to see their  paternal cousins face to face. The day has come. And, as I’ve imagined it 14 years ago, my kids are able to enjoy their moments with their kuyas as they easily converse with them about anything.

I feel accomplished.

17141253_10210757480164605_281625036_n

with the eldest among 5 paternal cousins

17125208_10210757463004176_16428245_n.jpg

with the second among 5 paternal cousins

 

 

Forgiving The Insecure and Fearful

Just as I and my classmate entered the conference room where our professor hold her small classes, our professor told us that the class really waited for us because somebody said that I, particularly blurting out my name, did not understand the requirement. There is a need to wait for us before the re-explanation of the requirement because I said I did not understand. I was actually gaping as I listened to it while putting down my bag and pulling out a chair to sit. What??? I know I never said such words to anyone. Even to me. I never said that I do not understand because I DO. Really there’s an urge to swear.

fearful.jpgSo, who is using my blessed name to cover up her own frailties? There is no man in our class, that’s why. Compassionate Lord, please tone down my temper, I silently prayed. Then the re-explanation by my professor was done. Still, my mind’s flying in the atmosphere trying to look for a logical sense in what I heard a while ago. Nonsense, I am not an oracle. But, we humans or because I belong to the sex of women, have the so called intuition. I have a hunch. I can feel it. And I remember a former colleague warning me about his present colleague’s greasing her way to the authority by bad-mouthing him. In one of my bus-rides towards CDO, I chanced to sit beside this male doctor in language. For the next two hours of bus mobility, we exchanged life and work updates. One of the topics mentioned was about the common women we now know.  Whoa, my mind’s telling me, is this now one of those antics of hers? My stomach churns I want to vomit. How low can she be.  Lo and behold, I can feel a bigger part of my brain saying just to let it slide and release understanding instead.

True enough, my wild beast side retreated in the recesses of my being. Wow. Had this been in my 20s and 30s, this would have been a riot. I am fearless when angered. I do not care who am I confronting. What was important to me is to ventilate my rightful wrath. To stand my ground. To not allow anyone step on my toes. I remember asking a cashier at a RTW store for scissors because I will cut to pieces the branded pants (Forenza) I already paid and another staff of the store assured me earlier that I can change size but ended up being told by the cashier that I can not change items. I’ve been looking for another size for an hour and a half and there’s no store plastered policy of no exchange. I was literally boiling that I did not mind the people lining up behind me at the counter. I demand for scissors! Then the manager approached my fiance (they know each other) and told him to pacify me while she assess the situation. I went down the store, Sureway, banging their door and walls. Then before my anger subsided I wrote and reported the whole incident to the main store office in Cebu. The following week I got a call from Cebu as they need to verify my letter. Then my fiance (now my husband as he never backed out despite seeing my bitchy side) went back to the store to claim new pants (for him already) and a poloshirt. Two items for one, sort of pacification consuelo de bobo for an unhappy customer.

That was what I’ve been. But, now I am learning to curb my beast mode. And instead, I am telling myself to forgive the fearful. This is about projection. So, okay, let me forgive. And, I like the wisdom of forgiveness in this way. “I forgive for my peace.”

annsayings-forgive-u