my world 2015: similarities, differences, and hidden priorities

DPUIC AND UNCT FOR THAILAND PRESENTS:

My World 2015: Similarities, Differences,

and Hidden Priorities An exploration of the data for Thailand

Dominic Bone

8/25/2014

The following report presents an analysis of the My World 2015 data set for the country of Thailand.

My World 2015: Similarities, Differences, and Hidden Priorities

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Project Team

Lead Researcher

Mr Dominic Bone – Dhurakij Pundit University International College –

[email protected]

Advisory Team

Prof. Dr Charles Newton – Dhurakij Pundit University International College

Dr Kiatanantha Lounkaew – Dhurakij Pundit University International College

Proof Readers

Steve Cannel – Dhurakij Pundit University International College

Supavadee Chotikajan – United Nations

(Please direct any questions or queries to Mr Dominic Bone)

mailto:[email protected]


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Contents

List of figures .............................................................................................................. 4

List of charts ............................................................................................................... 5

Introduction ................................................................................................................. 6

Structure of the report ................................................................................................ 7

Outreach strategy ................................................................................................... 7

Objectives .............................................................................................................. 8

Summary of findings .................................................................................................. 9

Results ...................................................................................................................... 11

Demographic overview of the Thailand dataset ....................................................... 11

Number of respondents ........................................................................................... 11

Source of data ..................................................................................................... 11

Source of data by sector ....................................................................................... 12

Gender of respondents ......................................................................................... 12

Education level of respondents ............................................................................. 13

Age of respondents .............................................................................................. 13

The My World 2015 priorities for Thailand ............................................................... 14

The top 6 priorities for Thailand ............................................................................ 14

The overall ranking of all 16 priorities for Thailand ................................................ 15

A description of each priority for Thailand ................................................................ 16

Priority #1 ‘A good education’ ............................................................................... 16

Priority #2 ‘A responsive government we can trust’ .............................................. 16

Priority #3 ‘Better Healthcare’ ............................................................................... 17

Priority #4 ‘Affordable and nutritious food’ ............................................................ 17

Priority #5 ‘Better job opportunities’ ...................................................................... 18

Priority #6 ‘Protection against crime and violence’ ................................................ 18

Priority #7 ‘Access to clean water and sanitation’ ................................................. 19


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Priority #8 ‘Phone and internet access’’ ................................................................ 19

Priority #9 ‘Protecting forests, rivers and oceans’ ................................................. 20

Priority #10 ‘Better transport and roads’ ................................................................ 20

Priority #11 ‘Equality between men and women’ ................................................... 21

Priority #12 ‘Support for people who cannot work ................................................. 21

Priority #13 ‘Reliable energy at home’ .................................................................. 22

Priority #14 ‘Freedom from discrimination and persecution’ .................................. 22

Priority #15 ‘Action taken on climate change ........................................................ 23

Priority #16 ‘Political freedoms .............................................................................. 23

The top 6 priorities by gender .................................................................................. 24

Females ............................................................................................................... 24

Males .................................................................................................................... 24

Homogenous yet heterogeneous ............................................................................. 25

Combinations of priorities ..................................................................................... 25

Groups sizes ........................................................................................................ 26

Similarities, differences, and hidden priorities ....................................................... 27

An exploration of gender preferences with educational groups ................................ 28

A comparison of young working age persons based on educational attainment ....... 30

Gender comparison within the ‘outside education system’ group ............................. 33

Conclusions .............................................................................................................. 34

General Limitations .................................................................................................. 36

General recommendations ....................................................................................... 37

References ................................................................................................................ 38

Appendix 1: Methodology ........................................................................................ 39

Appendix 2: A table of priorities .............................................................................. 45


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List of figures

Figure 1) My World 2015 ballot for Thailand

Figure 2) Overall ranking of all sixteen priorities

Figure 3) ‘A good education’

Figure 4) ‘A responsive government we can trust’

Figure 5) ‘Better healthcare’

Figure 6) ‘Affordable and nutritious food’

Figure 7) ‘Better job opportunities’

Figure 8) ‘Protection against crime and violence’

Figure 9) ‘Access to clean water and sanitation’

Figure 10) ‘Phone and internet access’

Figure 11) ‘Protecting forests, rivers and oceans’

Figure 12) ‘Better transport and roads’

Figure 13) ‘Equality between men and women’

Figure 14) ‘Support for people who cannot work’

Figure 15) ‘Reliable energy at home’

Figure 16) ‘Freedom from discrimination and persecution’

Figure 17) ‘Action taken on climate change’


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List of charts

Chart 1) Sources of data

Chart 2) Source of data by sector

Chart 3) Gender of respondents

Chart 4) Education level of respondents

Chart 5) Age distribution of respondents

Chart 7) Top six priorities chosen by the people of Thailand (%)

Chart 7) Top six priorities chosen by females (%)

Chart 8) Top six priorities chosen by males (%)

Chart 9) Occurring combinations of priorities

Chart 10) Occurring combination group sizes

Chart 11) Gender differences, similarities, and hidden priorities (gender and education)

Chart 12) Gender differences, similarities, and hidden priorities (outside vs inside education)

Chart 13) Gender differences, similarities, and hidden priorities (outside education: male vs. female)


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Introduction

MY World 2015 is a global survey led by the United Nations seeking respondents

to nominate six of the most important social development priorities for a better

world. The survey results will be shared with world leaders in setting the next

global development agenda.

Under the objective of engaging the Thai public in shaping the post-2015

development agenda, the UN Country Team (UNCT) in Thailand launched a

national campaign to promote the

‘MY World 2015’ survey during the

period January – December 2013.

The campaign aimed at boosting

the number of votes on

www.myworld2015.org as well as

engaging the wider Thai public on

the post-2015 development agenda

debate by adopting a social

mobilization and crowdsourcing

strategy, bringing together social

activists and bloggers to engage on

web platforms and social media on

the post 2015 choices. The MY World Thai language version was live as of 10

February 2013.

The United Nations, in partnership with over 60 other organizations, collected

over 69,000 online and offline responses in Thailand. The UNCT engaged

directly with the private sector, universities/schools, and civil society

organizations to organize several events and activities to reach out to individuals

and to encourage them to vote in MY World. The UNCT also contracted

MySocialMotion, a non-profit private company, to help support the MY World

National Campaign.

Figure 1) My World 2015 ballot for Thailand

http://www.myworld2015.org/


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The UNCT then partnered with Dhurakij Pundit University International College

(DPUIC), one of the active partners in the national campaign, to undertake an in-

depth analysis of the over 69,000 MY World votes in Thailand. DPUIC set out

to conduct a statistical analysis of the responses which aims to identify a clearer

demographic profile of each priority chosen and explore how these could guide

targeted policy responses.

Structure of the report

The report delivers a range of results and key findings relating to the analysis of

the Thailand data set. First, the report provides a demographic overview of the

data set followed by introduction of the top six priorities for Thailand. Next, the

sixteen priorities were arranged in a hierarchy (most chosen to least chosen) and

then the general patterns and characteristics of each priority based on gender,

education level, and age were described. The following section explores the

existence of groups who chose the same priority combination and the size of

these groups. The exploration of groups and combinations of priorities highlights

both the homogenous and heterogeneous characteristics of the data sample.

The next section provides a short outline of the gender differences in the choice

of the top six priorities.

The final part of the results and key findings section starts with a short discussion

of the limitations of only ranking as an approach to understanding the data. This

is followed by two analyses and discussions which are based on the application

of a novel approach to analyze the data from the perspectives of ‘gender and

education level’ and ‘working age youth’. The report concludes with a summary

of the key findings, an outline of the limitations, and some suggestions for further

research.

Outreach strategy

MY World national campaign targeted three main categories of partners to act as

multipliers for vote collection, namely private sector, education and civil society

organizations. The breakdown of the number of votes collected by category of

partners is as follows: education sector (44%); private sector (19%); civil society


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organizations (7%); MySocialMotion (12%); and UN in Thailand (8%). (See Chart

1).

The partners linked to the education sector gathered the highest number of votes

with a vibrant and creative network of student volunteers who reached out to their

peers, their local communities and prospective students (i.e. high school

students). DPUIC and Mahidol University gathered the largest number of votes

both through on- and off- campus activities, including road-shows and photo,

speech and video competitions.

Proctor & Gamble Ltd. (Thailand) was the biggest private sector partner, fully

incorporating the MY World campaign as part of their Corporate Social

Responsibility (CSR) program. Their outreach activities included staff voting,

engagement of their business partners, and community beneficiaries of the CSR

activities (including primary and secondary schools). MySocialMotion worked

with a core group of young professionals to serve as consultants in generating

interest and wider engagement in the post-2015 debate, including coordinating

volunteer committees to engage high schools, universities, and civil society

organizations also outreaching to the provinces through volunteers and local

communities. The UN in Thailand participated in a number of events organized

by the government and other UN agencies to set up MY World booths to

encourage the general public to vote on MY World.

Objectives

The purpose of the following report is to:

1. Introduce the My World 2015 global survey;

2. Identify and describe the My World 2015 respondents for the country of

Thailand;

3. Identify the top My World 2015 priorities for the country of Thailand;

4. Describe the response characteristics of each My World 2015 priority for

the country of Thailand;

5. Provide additional insights into the data sample for the country of Thailand;

6. Present an alternative analysis framework which goes beyond just ranking

the data.


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Summary of findings

The My World 2015 survey for Thailand collected 66,901 complete ballots.

The vast majority of data were collect via paper (57.5%) and online ballots

(34.5%).

The data were collected by: the education sector (n=29,377: 44%); the

private sector (n=19,439: 29%); a social enterprise called MySocialMotion,

(n=8,212: 12%); civil society (n=4,653: 7%); and the UN in Thailand

(n=5,220: 8%).

There are more female (59.4%) than male (40.6%) respondents.

Over half the sample have completed secondary education (51.8%) and

the other half (48.2%) are still with the education system or have exited

prematurely.

The sample population is young with the average age of 24-years old.

The top six priorities in descending order are “a good education”, “a

responsive government we can trust”, “better healthcare”, “affordable and

nutritious food”, “better job opportunities”, and “protection against crime

and violence”.

Each of the sixteen priorities displays unique characteristics relating to

gender, age group, and education levels.

The top six priorities as selected by males and females are identical albeit

in a slightly different order.

Further examination of the data identified both homogenous and

heterogeneous characteristics.

There is a set of top six ranked priorities which are important when

examining the data overall. However, the absolute ranking of priorities

provides limited insights.

There are 7537 identified different combinations of six priorities and of

those there are 984 unique ballots. This means that the sample is

heterogeneous and consists of a lot of small and different groups and is

not as homogenous as the ranking of priorities suggests.

The 10 largest groups only represent 1% of the total sample.


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There are gender specific differences, similarities, and hidden priorities

which cannot be identified through the ranking of priorities alone, for

example:

a. The priority of ‘equality between men and women’ was chosen in

greater proportions by all female groups at all levels of education

when compared to males and represents an important issue for

females.

b. Overall males are more concerned with ‘green’ issues when

compared to females.

c. There are differences between the expressed priorities of young

persons who are of working age and are either within the secondary

education system or outside of the education system although

these (specific) findings should be interpreted with caution as it

possible that erroneous data were collected.


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Results

The following section of the report describes the results and key findings. To

assist in the interpretation of the findings, the commentary is supported by graphs

and figures.

Demographic overview of the Thailand dataset

The My World 2015 survey employed a simple survey tool which, in addition to

labelling the respondents’ top six priorities also included their age, gender, and

education level. In addition to this, data were collected which identified how the

respondents completed the survey. The following section outlines each of these

four basic demographic properties and starts with an overview of the source of

data.

Number of respondents

A total of 66,901 (of 69,000) complete My World ballots were collected in Thailand

and this is about 0.1% of the 66.79 million Thai population (World Bank, 2012).

Source of data collection

The ‘My World 2015’ survey

employed four different

approaches to data collection.

The Thailand sample employed

all four approaches and

collected data offline via a paper

ballot (n=38,470: 57.5%), online

though the UN My World 2015

and partner websites (n=23,080:

34.5%), mobile application

(n=5,296: 7.9%), and via mobile

SMS service (n=55: 0.1%)

respectively.

Chart 1) Source of data


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Source of data collection by sector

To collect diverse data from

Thai society, the UN in Thailand

engaged with a variety of

stakeholders from different

sectors. The largest

contribution was made by the

education sector (n=29,377:

44%), followed by the private

sector (n=19,439: 29%).

MySocialMotion, a social

enterprise, contributed

(n=8,212: 12%).Civil society

contributed (n=4,653: 7%) and

the UN in Thailand added

(n=5,220: 8%).

Gender of respondents

The respondents from Thailand

are approximately 60% female

(n=39,756: 59.4%) and 40%

male (n=27,145: 40.6%).

Chart 3) Gender of respondents

Chart 2) Source of data by sector


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Education level of respondents

The Thailand sample ranged in

the level of educational

attainment with 8.1% (n=5,447)

starting but not completing

primary education, 22.5%

(n=15,064) completing primary

education, 17.5% (n=11,707)

starting but not completing

secondary education, and

51.8% (n=34,683) finishing

secondary education

Chart 4) Education level of respondents

Age of respondents

The age range of respondents is 94 years spanning from 5 years old to 99

years old with the average age of 24 years old. The median age is 20 years old

which means that 50% of the respondents are under 20 years old and 50% of

respondents are over 20 years old. The mode, or the most frequently occurring

age is 18 years old.

Chart 5) Age distribution of respondents


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The My World 2015 priorities for Thailand

The following section of the report identifies, describes, and discusses the

individual and collective profiles of the priorities chosen by the people of Thailand.

The top 6 priorities for Thailand

The top six priorities chosen by the people of Thailand are:

Chart 6) The top six priorities chosen by the people of Thailand (%)

The highest ranking priority “a good education” (n=46,782) was chosen by about

seven out of ten persons in the Thailand sample. The following second and third

place priorities of “a responsive government we can trust” (n=36,255) and “better

healthcare” (n=34,157) were chosen by about five out of ten, or half of the,

persons within the Thailand sample. The fourth, fifth, and sixth place priorities of

“affordable and nutritious food” (n=27,418), “better job opportunities” (n=27,052),

and “protection from crime and violence” (n=26,643) were chosen by about four

out of 10 persons


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The overall ranking of all 16 priorities for Thailand

The following section begins to explore the basic characteristics of the data in

relation to each of the sixteen My World 2015 priorities. First, we introduce the

overall ranking for the complete set of sixteen priorities, and this is followed by a

demographic description of each priority (rank/count/percentage) and a summary

of relationships between the gender, age, and education categories.

Figure 2) Overall ranking of all sixteen priorities

#1 "A good education"

#2 "A responsive government we

can trust"

#3 "Better healthcare"

#4 "Affordable and nutritious food"

#5 "Better job opportunities"

#6 "Protection against crime and

violence"

#7 "Access to clean water and sanitation"

#8 "Phone and internet access"

#9 "Protecting forests, rivers and

oceans"

#10 "Better transport and

roads"

#11 "Equality between men and

women"

#12 "Support for people who can't

work"

#13 "Reliable energy at home"

#14 "Freedom from

discrimination and persecution"

#15 "Action taken on climate

change"

#16 "Political freedoms"


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A description of each priority for Thailand

The following section summarises each of the 16 priorities and is constructed

from the identifiable trends and patterns found within the data sample.

Priority #1 ‘A good education’

Overall ‘a good education’ is the most frequently selected priority and is chosen

by 69.9% (46,782) of the respondents. However, it is ranked number #3 within

the >=61 age category.

Figure 3) ‘A good education’

Priority #2 ‘A responsive government we can trust’

‘A responsive government we can trust’ is the second place priority and is chosen

by 54.2%(36,255) of the respondents.

Figure 4) ‘A responsive government we can trust’


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Priority #3 ‘Better Healthcare’

Overall ‘better healthcare’ is the third place priority chosen by 54.2% (36,255) of

the respondents. However, it is ranked number #2 within the >=61 age category.

There is a two-step age related pattern with a noticeable jump occurring between

the 16-30 and 31-45 age categories.

Figure 5) ‘Better healthcare’

Priority #4 ‘Affordable and nutritious food’

‘Affordable and nutritious food’ is in the fourth place chosen by 54.2% (36,255) of

the respondents.

Figure 6) ‘Affordable and nutritious food’


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Priority #5 ‘Better job opportunities’

‘Better job opportunities’ is the fifth place priority chosen by 36,255 (54.2%)

respondents.

Figure 7) ‘Better job opportunities’

Priority #6 ‘Protection against crime and violence’

‘Protection from crime and violence’ is the sixth place priority chosen by 36,255

(54.2%)respondents.

Figure 8) ‘Protection against crime and violence’


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Priority #7 ‘Access to clean water and sanitation’

‘Access to clean water and sanitation’ is the seventh place priority chosen by

25,577 (38.2%) of the respondents. Females in the >=61 age and the ‘started

primary’ categories are much higher than both male and all other female age

categories.

Figure 9) ‘Access to clean water and sanitation’

Priority #8 ‘Phone and internet access’’

‘Phone and internet access’ is the eighth place priority chosen by 24,564 (36.7%

of the respondents. An interesting characteristic of this priority is the <=15 age

group who chose this priority twice as much as the >=61 age group.

Figure 10) ‘Phone and internet access’


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Priority #9 ‘Protecting forests, rivers and oceans’

‘Protecting forests, rivers and oceans’ is the ninth place priority chosen by 24,098

(36%) of the respondents. This is a very interesting priority and it was chosen by

males more than females. There is also a gender relationship with education

level. Males choose this priority more as they achieve higher levels of education.

The opposite occurs for females; as females become more educated, they

choose this priority less frequently.

Figure 11) ‘Protecting forests, rivers and oceans’

Priority #10 ‘Better transport and roads’

‘Better transport and roads’ is the tenth place priority chosen by 23,970 (35.8%)

of the respondents. Interestingly, this priority is particularly important to females

>=60 years old.

Figure 12) ‘Better transport and roads’


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Priority #11 ‘Equality between men and women’

‘Equality between men and women’ is the eleventh place priority chosen by

20,288 (30.3%) of the respondents. This priority is chosen more by females

within all age groups and at all levels of education. Furthermore, it is most

important to the ‘finished primary’ group and gradually declines as education

levels rise.

Figure 13) ‘Equality between men and women’

Priority #12 ‘Support for people who cannot work

‘Support for people who cannot work’ is the twelfth place priority chosen by

19,931 (29.8%) of the respondents. Overall, this priority is more important to

males than females but becomes more important to females as they get older.

Figure 14) ‘Support for people who cannot work’


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Priority #13 ‘Reliable energy at home’

‘Reliable energy at home’ is the thirteenth place priority chosen by 17.403

(26.0%) of the respondents. Overall, this priority is more important to males but

becomes more important to females as they get older.

Figure 15) ‘Reliable energy at home’

Priority #14 ‘Freedom from discrimination and persecution’

‘Freedom from discrimination and persecution’ is the fourteenth place priority

chosen by 17.352 (25.9%) of the respondents.

Figure 16) ‘Freedom from discrimination and persecution’


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Priority #15 ‘Action taken on climate change

‘Action taken on climate change’ is the fifteenth place priority chosen by 15,789

(23.6%) of the respondents.

Figure 17) ‘Action taken on climate change’

Priority #16 ‘Political freedoms

‘Political freedoms’ is the last out of the sixteen priorities chosen by 14,127

(21.1%) of the respondents.

Chart 12) ‘Political freedoms’


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The top 6 priorities by gender

The following section summarises the top six priorities as chosen by each gender.

Females

The top six priorities and order chosen by females are identical to the ranking of

those for the whole of the Thailand sample.

Chart 7) The top six priorities chosen by females (%)

Males

The top six priorities chosen by males are identical to those for the whole of the

Thailand sample except that “better job opportunities” and “affordable and

nutritious food” have swapped positions.

Chart 8) The top six priorities chosen by males (%)


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Homogenous yet heterogeneous

An initial observation of the top six ranked priorities indicates that the selection of

top priorities is made in a very homogenous fashion. It is true that a minimum of

40% and a maximum of 70% of the sample chose each of the top six priorities

and that both genders selected the same top six; albeit in a slightly different order.

However, the following discussion and charts describe how the data have a range

of heterogeneous characteristics.

Combinations of priorities

There are a possible 8008 unique combinations of six out of sixteen priorities.

The Thailand data set exhibits 7537 different chosen combinations of priorities,

and there are an additional 471 combinations of priorities that are not chosen. Of

the 7537 identified combinations, there are 984 uniquely chosen combinations,

i.e. chosen by only one respondent (equal to about 0.7% of the sample).

Chart 9) Occurring combinations of priorities


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Groups sizes

An examination of the number of each of the 6553 identified combinations which

have more than one identical response yields very interesting findings. Out of the

66,901 responses for Thailand, it is found that the largest group has only 207

identically chosen ballots and this group represents a mere 0.003% of the whole

sample. In fact, the 10 largest groups ranging from 131 to 207 identical responses

represent less than 1% of the entire sample. Over 80% of the groups of identically

chosen ballots contain 10 or less responses.

Chart 10) Occurring combination group sizes

If the sample were truly homogenous, one would expect to find larger numbers

of identical ballots.

But what does this mean?

Combining these facts delivers one of the most important findings of the study.

On the one hand, the Thai sample is very homogenous in that there is a core set

of highly ranked priorities (the top six), and on the other hand, there is also a great

deal of variation in the ranking (the lack of large groups and the diversity of small

groups). In fact, numerous more detailed analyses of the sample data were


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conducted following this discovery (these are beyond the scope of this report)

and these have also identified a great deal of variation hidden behind the ranking.

The following conclusion may be drawn. It is true that, overall, the top six are

important, but the ranking suggests that the top six ‘ranked’ priorities are really

the most important for all. However, evidence indicates that this is not the case,

and that there is no single set of priorities which is important to all. In reality,

there is a different set of concerns for different people.

Similarities, differences, and hidden priorities

Simply counting the number of times a priority is chosen produces a count so that

a ranked position can be identified for each priority relative to the other priorities.

Examining the ranking of priorities by segmenting the sample by gender or

education level does provide some initial insights into the data. However, in an

attempt to extract more detailed insights, a novel data transformation and

statistical analysis was conducted using the Chi-square (X2) goodness-of-fit-test

statistic. Chi-square analysis of the data was conducted to show how

demographic factors influenced the choice of the different development priorities.

The analysis shows that specific issues (beyond the three top ones), are much

more (or less) likely to be chosen based on gender, regardless of education

status and age. Likewise, differences are registered among young people

whether they have entered the workforce or are still attending school. “

In addition, the variances (measured differences) can also be plotted on a graph

to provide a visual representation of both the differences and similarities within

the data. Each priority can then be labelled as either being selected in the same

proportion (a similarity) or in differing proportions (a difference). Furthermore, it

is possible to identify whether there are hidden priorities within each group. A

hidden priority is defined as a priority which is underrepresented by examining its

ranked position alone. For example, a low ranked priority may be chosen in

greater proportions by a specific gender in all age or education categories. This

indicates an important ‘unseen’ relationship when considering the ranked position

alone.


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The following section presents the findings of two of these analyses. The first is

a comparison of gender responses throughout the general education life cycle.

The second explores the differences between young working age persons and is

split by whether they are attending school or have exited early and are potentially

within the national workforce.

An exploration of gender preferences with educational groups

The proportions of the male group were compared to those of the female group

using the Chi-square (X2) goodness-of-fit-test statistic. The Chi-square (X

2)

goodness-of-fit-test statistic identified that overall the two groups have statistically

different proportions in the selection of priorities. In other words, there are

identifiable gender differences in the selection of priorities. The simplest way to

present the significant differences and similarities is by using a variance chart.

hart 11) Gender differences, similarities, and hidden priorities (gender and education)

Chart 11 above displays the variance between the ‘male’ group and the ‘female’

group. The further from the central line the coloured bar extends, the greater is

the degree of variance when compared to the other group. In other words, the

longer the coloured bar is, the greater is the proportion of respondents who chose

a given priority when compared to the proportions of the other group who chose

it. The closer the coloured bar is to the central line, the greater is the degree of

similarity between the groups.


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A number of interesting observations can be made from the above chart:

1. Four of the top six priorities were chosen in equal proportions by both

males and females. This means there are similarities. The similarities are

‘a responsive government we can trust’, better healthcare’, ‘affordable and

nutritious food’, and better job opportunities’.

2. Two of Thailand’s top six priorities ‘a good education’ & ‘protection from

crime and violence’ are important to both genders but, overall, they are

more important to females.

3. None of the top six priorities were chosen in greater proportions by males.

4. There are a number of priorities which have a statistically significant

gender importance which is unidentifiable within the absolute ranking of

the priorities.

a. The priority which was chosen in the most statistically significant

proportions by females at all education levels when compared to

males, is ‘equality between men and women’. Gender equality

ranked in 11th place overall and this female priority was hidden

within the absolute ranking. ‘Access to clean water and sanitation’

is ranked in 7th place in the absolute ranking.

b. The priority which was chosen in the most statistically significant

proportions by males at all education levels when compared to

females, is ‘political freedoms’ which was ranked in last place (16th)

overall in the absolute ranking. Males also chose ‘freedom from

discrimination and persecution’, ‘reliable energy at home’, ‘action

taken on climate change’, and ‘better transport and roads’ in greater

proportions.

5. An additional observation is that men seem to be much more concerned

about green issues as the males displayed in statistically significant

proportions that ‘action taken on climate change’ and an overall, but non-

significant greater proportion for ‘protecting forests, rivers and trees’.


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A comparison of young working age persons based on educational

attainment

The Thailand sample contains data collected from 17,899 young persons who

are aged between 15 and 18 years old. It is possible that there are differing

priority needs for young persons who are currently within, or recently exited after

completing secondary education and those who only partially completed or

completed only primary education. The group of young persons who are outside

the education system are of legal working age in Thailand. The legal minimum

age for employment in Thailand is 15 years old. These two subsamples consist

of 8,259 young persons who are of working age and outside the education system

and 9,640 young persons who are of working age and inside the education

system, or have very recently finished. The following section compares and

contrasts the responses of young persons who are of working age and are either

within the secondary education system or outside the education system (and

possibly working). The criteria for inclusion in the analysis are as follows:

Age is >=15 years old and <=18 years old,

And,

Outside education system - Either completed primary level (finished

primary) or exited the primary education system prematurely (some

primary). There are 8259 respondents who fall into this category.

Or,

Inside education system or very recently finished - Either within the

secondary education system (some secondary) or recently completed

(finished secondary). There are 9640 respondents who fall into this

category.

Analysis limitations:

Due to limitations in the data and the data collection process the following two

factors need to be considered when interpreting the following results and

commentary:


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1. The number of respondents who reported their educational attainment as

‘finished primary’ and are aged between 15 and 18 years is very high. It is

highly probable that this includes erroneously collected data. However, it

is not possible to prove the contrary. The following result analysis should

be interpreted with caution.

2. It is not possible to identify those who exited the secondary education

system prematurely and an assumption is made that those who have

reported ‘some secondary education’ are currently still within the

education system.

Chi-square analysis

The proportions of the ‘outside education system’ group were compared to those

of the ‘inside education system or very recently finished’ group using the chi-

square (X2) goodness-of-fit-test statistic. The chi-square (X

2) goodness-of-fit-test

statistic identified that, overall, the two groups have statistically different

proportions in the selection of priorities. The simplest way to present the

significant differences and similarities is by using a variance chart.

The following variance chart displays the variance between the ‘outside

education system’ group and the ‘inside education system or very recently

finished’ group. The further from the central line the coloured bar extends, the

greater is the degree of variance when compared to the other group. In other

words, the longer the coloured bar is, the greater is the proportion of respondents

who chose a given priority when compared to the proportion of the other group

who chose it. The closer the coloured bar is to the central line, the greater is the

degree of similarity between the groups.


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Chart 12) Gender differences, similarities, and hidden priorities (outside vs inside education)

A number of observations can be made from the above chart:

1. The proportions of six priorities are chosen in statistically similar

proportions and represent the greatest degree of similarity between the

two groups. These are ‘a good education’, ‘reliable energy at home’,

protection against crime and violence’, ‘affordable and nutritious food’,

‘access to clean water and sanitation’, and ‘ phone and internet access’.

2. The greatest concerns of the ‘outside education group’ are “equality

between men and women”, “action taken on climate change”, “better job

opportunities”, and “support for people who cannot work”. On face value

alone, young persons lacking both education and working experience

would select both “better job opportunities” and “support for people who

cannot work” as important personal concerns when considering the

probable hardships they would encounter in such a situation.

3. The greatest concerns of the ‘inside education system or very recently

finished’ group are “a responsive government we can trust”, “political

freedoms”, “better health care”, and “protecting forests, rivers, and trees”


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Gender comparison within the ‘outside education system’ group

An intra-group gender comparison of the proportions of the ‘outside education

system’ group was compared to those of the ‘inside education system or very

recently finished’ group using the chi-square (X2) goodness-of-fit-test statistic.

The chi-square (X2) goodness-of-fit-test statistic identified there to be statistically

different proportions in the selection of priorities by each gender in the ‘outside

education system’ group.

The following variance chart displays the priority selection variances between the

male and female respondents of the ‘outside education system’ group.

Chart 13) Gender differences, similarities, and hidden priorities (outside education: male vs female)

A number of observations can be made from the above chart:

1. There are six priorities which have been chosen in statistically similar

proportions. These are ‘phone and internet access’, ‘clean water and

sanitation’, ‘affordable and nutritious food’, ‘support for people who cannot

work’, ‘better healthcare’, and ‘better job opportunities’. These priorities

represent similarities between the two groups.

2. It may be important to consider that both genders have a similar need for

“better job opportunities” and “support for those who cannot work


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3. The female respondents in this group placed emphasis on “equality

between men and women”, “a good education”, and the two politically

focussed priorities of “a responsible government we can trust” and

“political freedoms”.

4. The males, conversely, chose ”protection from crime and violence” and,

amongst other priorities placed emphasis on the green issues of

“protecting forests, rivers, and oceans” and “action taken on climate

change,”

Conclusions

Data collected for the My World 2015 survey has shown that about 0.01% of the

Thai population took the opportunity to vote. The data were primarily collected

on paper ballots (57.5%) rather than online ballots (34.5%) by a range of

stakeholders from the education sector (n=29,377: 44%); the private sector

(n=19,439: 29%); a social enterprise called MySocialMotion, (n=8,212: 12%); civil

society (n=4,653: 7%); and the UN in Thailand (n=5,220: 8%).

The respondents are mostly female (59.4%) rather than male (40.6%) with an

average age of 24-years old. Over half the respondents have completed

secondary education (51.8%) and the other half (48.2%) are either still in the

education system or have exited prematurely.

The top six My World 2015 priorities for Thailand (in descending order) are “a

good education”, “a responsive government we can trust”, “better healthcare”,

“affordable and nutritious food”, “better job opportunities”, and “protection against

crime and violence”. The same top-six combination is chosen by males and

females. However, each of the sixteen priorities displays unique characteristics

relating to gender, age group, and education levels. For example, as persons

become older ‘a good education’ becomes less important and conversely ‘better

healthcare’ becomes more important. However, this supports what one would

expect to see based on the face values attached to the priority. It is interesting

that males place more importance on the green priorities of ‘protecting forests,


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rivers and oceans” and ‘action taken on climate change. Furthermore, although

‘a responsive government we can trust’ is the number 2 priority ‘political

freedoms’ comes in last position as priority number sixteen.

Ranking the My World 2015 data does provide valuable information about what

is of overall importance to the Thai people based on the collective preference for

specific priorities. However, whilst ranking segments the Thailand sample into

large homogenous groups for individual priorities, it does not provide any insights

into the relationships and connections between the combinations chosen by the

Thai people. In an attempt to yield insights beyond the limitations of ranking,

further analyses of the data were conducted and these have identified both

homogenous and heterogeneous characteristics. There are 7537 identified

different combinations of six priorities and of those there are 984 uniquely chosen.

Somewhat surprisingly, the sample does not contain any large groups and the

largest group contains only 207 identical ballots. In fact, the top 10 largest groups

represent less than 1% of the whole sample. This is a very important finding as

it indicates that there is no single set of priorities which is important to all the

people of Thailand. The analysis also identified a range of priorities which are

selected in greater proportions based on gender. For example, females in all age

groups and at all education levels choose ‘equality between men and women’ in

greater proportions than males. The 11th place ranking of ‘equality between men

and women’ does not reflect the overall importance of this priority for the females

of Thailand. Conversely, ‘political freedoms’ which was ranked in last place (16th)

overall in the absolute ranking was chosen by males in greater proportions when

compared to females. Neither of these observations can be made through ranking

alone.

The final conclusion is there is a top six set of priorities which is more important

overall to the people of Thailand. However, there is also a great deal of variation

within the chosen combinations and in reality, this reflects a very different set of

often unique concerns for different people.


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General Limitations

The sample is biased toward a young age group and does not represent

the full age diversity of Thailand’s population.

Ranking the data does provide insights into which priorities are the most

important overall. However, ranking alone fails to identify priorities for

individual groups.

Response error and misunderstanding of the survey may have contributed

to the loss of valuable data and may have also contaminated the findings.

The responses are probably influenced by current affairs and may be more

reflective of the opinions at the time the data was collected.

The ‘My World 2015’ data set consists of mostly nominal data which

generally restricts the use of the more powerful parametric statistical

procedures. Thus many of the insights are limited to measures of central

tendency (mean, mode etc) and ranking. This is an opportunity lost.

However, on the flip side, one must consider the challenges of collecting

data on a global scale and whether it is feasible to attempt to diversify the

data collection tools.

Individual responses and clusters of responses cannot be classified as:

urban vs. rural; ethic grouping; disabilities; or as specific geographic

regions of Thailand. Therefore, the available data do not allow for more

than national generalisations.

Data transformations and the application of novel analysis techniques can

provide additional insights. However, these may be open to differing

interpretations. The author has attempted to be as objective as possible.

Ultimately, the collection of superior geo-demographic data would have

been a better option.

There are a number of other statistically significant relationships which

were revealed during the process of data analysis. However, due to

limitations with the data set, it is very difficult to provide a useful or practical

application of these findings.

The data set is huge and has much more potential for analysis and this

report has really only scratched the surface. However, one must ask what


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is the ‘return on investment’ when it comes to extending the analysis

further.

The responses are probably influenced by current affairs.

General recommendations

To share the findings of this report with the Thai people.

To apply the concepts learnt throughout this data analysis project to other

sub-samples of the My World 2015 data set.

To analyse the ASEAN data set in more detail.

To collect more comprehensive geo-demographic data in subsequent

studies of this type.


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References

World Bank (2014) Data: Population total.

http://data.worldbank.org/indicator/SP.POP.TOTL

United Nations (2014). Have your say. http://vote.myworld2015.org/

http://data.worldbank.org/indicator/SP.POP.TOTL

http://vote.myworld2015.org/


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Appendix 1: Methodology

An array of statistical techniques was used to analyze the My World 2015 data

set for Thailand. Some of the analyses applied were very simple (such as the

calculation of average values, ranking, and percentages) and others required the

application of novel techniques that were used in an attempt to yield additional

insights (binary clustering and the data restructuring technique). The data set

has a number of limitations, primarily relating to the narrow range of geo-

demographic data collected, and as a consequence, some novel data

transformations and techniques were applied in an attempt to yield additional

insights.

This report was written with the intention of being in a ‘simple to read’ format.

However, this methodological section has been included for those readers who

may be interested in the techniques applied during the analysis.

Sample size and sampling window

The ‘My World 2015’ global data set contains over 1.5 million votes and can be

downloaded from the ‘My World 2015’ Data Repository

(http://54.227.246.164/dataset/). The data for Thailand used in the following

analysis were collected between 11th January, 2013 and 15th December, 2013.

The data set for Thailand consists of n=66,901usable cases and this sample

equates to about 0.1% of the 66.79 million population of Thailand (World Bank,

2012). The following data analysis methodology will be separated in several

sections based on the types of analysis to be conducted.

Data cleaning

Data coding

Basic descriptive analysis

Thailand priority ranking

Binary clustering analysis

Combination matrix

Largest cluster analysis

http://54.227.246.164/dataset/


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Priority profiles

Priority cluster profiles

Data restructuring, frequency distribution, and chi-square methodology

Gender and priorities (a second look)

Data Cleaning

The data set is cleaned in Microsoft Excel and Microsoft Access by removing

cases with missing, dummy, and/or other variable discrepancies. The data set is

analysed using Microsoft Excel, Statistical Package for Social Scientists (SPSS),

and other statistical analysis software as required.

Data Coding

The data set is coded and a complete codebook is available upon request (it

would accompany the data set). However, the 16 priorities are coded as follows:

Priority Code

"Action taken on climate change" 100

"Better transport and roads" 101

"Support for people who can't work" 102

"Access to clean water and sanitation" 103

“Better healthcare” 104

“A good education” 105

“A responsive government we can trust” 106

"Phone and internet access" 107

"Reliable energy at home" 108

“Affordable and nutritious food” 109

"Protecting forests, rivers and oceans" 110

“Protection from crime and violence” 111

"Political freedoms" 112

"Freedom from discrimination and persecution" 113

"Equality between men and women" 114

“Better job opportunities” 115

Basic Descriptive Analysis

An initial explorative summary of the demographic variables and the response

profiles for each of the My World 2015 priorities will be performed. The analysis

included measures of central tendency (mean, median, and mode) and measures

of dispersion (frequency distribution (counts and percentages), standard

deviation, range, minimum, maximum, kurtosis and skewness). Age data are


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analysed as both a continuous (ratio) variable and as a binned (categorical)

variable (using the bin ranges presented on the ‘My World 2015’ website analysis

page). Relevant and appropriate results are presented in both graphical and

tabular formats with additional cross-tabulations as appropriate.

Binary Clustering Methodology

The data are not appropriate for traditional clustering techniques. Therefore, the

approach used to identify response patterns and potential clusters will be based

on concepts taken from evolutionary computational techniques. This approach

will further overcome some of the inherent limitations of the initial data set and

open further avenues to more accurate and advanced statistical procedures. The

clustering methodology will be outlined in the following paragraph.

The My World 2015 survey asks respondents to select 6 out of 16 predetermined

priorities. These are not ranked selections but merely choices. Therefore, the

priority selection data are binary as each priority has one of two mutually

exclusive states. It is chosen (1) or not chosen (0). The raw data from each ballot

are converted into a 16-bit binary string (for example 1111000100000001) with

each chosen priority being represented by a ‘1’ and the other not-chosen priorities

being represented by a ‘0’. Each binary string is converted into an identifiable

‘combination code’ using positive exponents which multiply the individual ‘bits’ of

each binary string, which produces a unique identifiable coded value for each bit,

for example:

100: 1 *2^15 = 32,768

101: 1 *2^14 = 16,384

102: 1 *2^13 = 8,192

103: 1 *2^12 = 4,096

107: 1 *2^8 = 256

115: 1 *2^0 = 1

Combination Code = 61,697


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All cases can be sorted according to their unique combination code and the

calculated frequency statistics. This effectively clusters each combination of

priorities into homogenous groups of choices. Frequency and descriptive

statistics of the combinations of the respondents can be produced as per the

profile presented in the basic descriptive statistics section of the methodology.

Combination Matrix

Using a binomial coefficient (see below), it is possible to calculate that there are

8008 possible combinations for 6 of 16 choices.

A combination matrix can be created in Microsoft Excel using a (modified 3 rd

party) VBA macro. Combinations of cases can be matched to the matrix to identify

occurring and non-occurring combinations. Descriptive statistics are calculated

in SPSS to initially describe the patterns of frequency and distribution occurring

in the data sample. It is also possible to identify combinations which are not

occurring in the sample.

Largest Cluster Analysis

The 10 largest groups are identified, analysed, and discussed. Tables and graphs

will be presented as appropriate.

Priority profiles

A review of each of the 16 priorities is presented, analysed, and discussed. The

description of each priority has the following format:

1. A demographic summary (see basic descriptive analysis above for details)

2. A cross-tabulation analysis (‘selected’ versus ‘not selected’ by binned age

category and then by education category) and a concurrent stacked

(100%) bar graph analysis to indicate basic trends and patterns in the data

3. A description of the key defining characteristics


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4. A subjective narrative attempting to provide insights into the priority

5. Tables and graphs will be presented as appropriate.

Data restructuring, frequency distribution, and Chi-square (X2)

methodology

The data set is partitioned into segments by priority, clusters of priorities, or size

and then further partitioned by education level, gender, and source. To create a

histogram and frequency distribution for each of the segments’ six priorities, the

priority set for each segment is restructured from six separate variables and

merged into one single variable. This does not create a real continuous variable

and the histogram is not a distribution in the common sense. However, by

ordering the variables in this way, it is possible to compare and contrast the

separate segments in a number of different ways. Firstly this is achieved by

compiling visual collections of each segment and their histograms to see if there

are any visually observable differences in priority selection, education level,

gender, and source for each grouped collection and when compared to the other

segmented groups. Secondly, by harvesting the frequency distribution data and

creating data tables in Microsoft Excel, it is possible to perform chi-square

‘goodness of fit’ statistical tests. The chi-square statistic (X2) calculates whether

there is a significant relationship between two categorical variables (the segment

histograms are actually ordered frequency distributions for the collective totals of

each segments categorical six binary priority choices). The chi-square test

statistic uses the following formula:

The data from each segment pass the two assumptions of the chi-square test in

that it is both categorical and will examine two or more independent groups. The

specific application of the chi-square statistics is the goodness of fit test which

will assesses whether data come from a known distribution, or in other words are

the observed proportions comparable to a known set of proportions. The known


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distribution (proportions) will either be the data set for the whole of Thailand

(priority, education level, gender, or source), or a specified segment, minus the

set of data to be observed. In the case of inter-priority comparisons by gender,

the female distribution will be classified as the known distribution (set of

proportions). The alpha significance level for all tests is set at p =<.05. Results

are presented in a visual format for easy reading.


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Appendix 2: A table of priorities

Symbol key: = greater/increasing; = lesser/decreasing; = equal

Priority Age Education Gender

#1 "A good education"

(n=46,782/69.9%)

importance to young

importance with age

importance to those with lower levels of education

importance to young females when compared to young males

importance in older males and females

#2

"A responsive government we can

trust"

(n=36,255/54.2%)

importance with age

importance as education levels increase

importance to males when compared females

importance to older males (>=61 years) when compared to all other groups

#3 "Better healthcare"

(n=34,157/51.1%)

importance to young <=30 years

importance at 30 years

importance in all age categories >=30 years

importance in the ‘started primary’ and ‘finished secondary’ groups

importance to males and females

#4

"Affordable and nutritious food"

(n=27,419/41.0%)

importance in all age categories

importance in all education categories, except;

importance in the ‘started primary’ group

importance to young males (<=15)

importance to females (>=31 to <=60)

#5

"Better job opportunities"

(n=27,052/40.4%)

importance to young within the 16-31 years age category

importance with age, particularly the >=61 years age group

importance in all education categories, except;

importance in the ‘finished secondary’ group.

importance to females in all age categories >=31 years old.

importance to females in the ‘finished secondary’ categories


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#6

"Protection against crime and violence"

(n=26,643/39.8%)

importance to young age <16 years

importance in all age categories from age >=16 years

importance through ‘started primary’ to ‘finished primary’ group

importance in all other education categories

importance in both genders, except;

importance in the female ‘finished primary’ group when compared to the males

#7

"Access to clean water and sanitation"

(n=25,577/38.2%)

Although the <=15 age group was noticeable high this priority becomes progressively more important in the older age groups.

importance to the ‘started primary’ and ‘finished primary’ groups

Overall, as females’ age they are more concerned with this priority than males. Females in the >=61 age and the ‘started primary’ categories are much higher than both males and all other female age categories.

#8

"Phone and internet access"

(n=24,564/36.7%)

This priority is much more important to young persons and reduces with age with a notable reduction from 31-45 age group onwards. The <=15 group is double that of the >=61 group.

importance to the ‘finished primary’ group

importance in both genders

#9

"Protecting forests, rivers and oceans"

(n=24,098/36.0%)

There is a general trend for young adults and middle aged persons to be more concerned with this priority.

importance in all education categories

importance to males

importance as males progress though the education levels

importance as females progress though the education levels

#10

"Better transport and roads"

(n=23,970/35.8%)

importance to the 16-30 age group and gradually declines as age progresses

importance as education levels increase

importance to males<60 years old

importance to females =>60 years old


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#11

"Equality between men and women"

(n=20,288/30.3%)

importance to both younger and age groups

importance to ‘finished primary’ group followed by a gradual decline as education levels rise

importance to females in all age groups and at all education levels.

This priority is, however, notably highest in the <=15 age group for both genders.

#12

"Support for people who can't work"

(n=19,931/29.8%)

importance with age; notably in the>=60 years group

importance in the ‘started primary’ group

importance in all other education categories

importance to males overall; notably at >=60 years

importance to females as they become older

#13

"Reliable energy at home"

(n=17,403/26.0%)


importance to lower education levels

importance to males overall

importance to females as they become older

#14

"Freedom from discrimination and

persecution"

(n=17,352/25.9%)

importance to young<=30 years

importance with age>=31 years


importance to males overall; particularly in the 15-30 age group

#15

"Action taken on climate change"

(n=15,789/23.6%)



importance to males overall; particularly in the ‘finished primary’ group

#16 "Political freedoms"

(n=14,127/21.1%)

importance in all age categories>=15 years

importance as primary education progresses, then

importance in secondary education

importance to females in the higher education levels

my world 2015: similarities, differences, and hidden priorities

Documents

thailand presents

thailand dominic bone

hidden priorities

country of thailand

thailand dataset

source of data

data set

number of respondents