Home Study 1 Study 2 Study 3

Dissertation Prospectus

Erika Sanborne, Sociology PhD Candidate, University of Minnesota

Committee: Elizabeth Heger Boyle (Chair); Joan DeJaeghere; Phyllis Moen; and Tom VanHeuvelen

Title: (tbd)

disabled people at work

Study

1

Disabled Development

Where are Disabled Women amidst the Sustainable Development Agenda in Costa Rica?

Study

2

cartoon explainer of disability variables and regression models

Social Model of Disablility Operationalization

Including measures of access when disaggregating data by disability can highlight crucial development-disability gaps.

Study

3

SDG 10 Reduced Inequalities

National Disability Policy Analysis

How does the nature of national disability legislation relate to the educational attainment potential of disabled women?

Acknowledgements

My complete reference list is below. Please find here my sources of support: people, funding, data, and technology. While these valuable contributors aided this research with their support, any errors are solely mine.

My Committee

Elizabeth Heger Boyle (Chair); Joan DeJaeghere; Phyllis Moen; and Tom VanHeuvelen

IPUMS MICS Data

Anna Bolgrien, Elizabeth Heger Boyle, Matthew Sobek, and Miriam King. IPUMS MICS Data Harmonization Code. Version 1.1 [Stata syntax]. IPUMS: Minneapolis, MN. , 2024. https://doi.org/10.18128/D082.V1.1
Learn more about my use of this data in my Methods Discussion: About IPUMS MICS.

User-written Stata Programs

I am grateful for the generous work and numerous, user-written programs and demos from Nick Cox (so many things); Ben Jann (i.e. coefplot, estout); J. Scott Long (i.e. SPost13); Richard Williams (gologit2)

All the Funding Sources

I appreciate support from the Minnesota Population Center (P2C HD041023), funded through a grant from the Eunice Kennedy Shriver National Institute for Child Health and Human Development (NICHD). IPUMS PMA is funded by the Bill & Melinda Gates Foundation. Additional support came through IPUMS DHS (NICHD R01HD069471) and IPUMS MICS (NICHD R01HD099182).

About IPUMS MICS

This research will analyze the IPUMS MICS Round 6. IPUMS MICS harmonizes Multiple Indicator Cluster Surveys (MICS) allowing comparative studies through consistent coding of variables.

The primary data for Study 1 and Study 2 come from a cross-sectional, nationally representative survey of Costa Rican households, with women aged 15-49 (n=8217 women). Interviews were conducted from March to May 2018 by Instituto Nacional de Estadísticas y Censos (INEC), under the design guidance of the United Nations Children’s Fund (UNICEF) (Bolgrien et al. 2024; National Institute of Statistics and Censuses and UNICEF 2018).

MICS employs a two-stage stratified sampling method to ensure broad demographic representation. Initially, geographic areas within Costa Rica are classified into urban and rural strata, from which clusters are randomly selected based on enumeration areas from the most recent censuses. Subsequently, households within each cluster are systematically chosen for inclusion in the survey. (UNICEF 2019).

For the women’s survey, all women aged 15-49 residing in the selected households as of the night before the survey were eligible for inclusion. Participants were informed about the survey’s scope and that their participation, requiring approximately 25 minutes, was voluntary and based on informed consent. Interviews take place in person, verbally, and the interviewer records responses on a digital tablet.

MICS surveys typically have sufficient sample sizes to produce representative data at both the national and subnational levels, including distinctions between urban and rural settings. The main objective of MICS is to generate actionable data on critical well-being indicators for women and children to inform policies and programs.

These data are also central to monitoring over 30 indicators related to the Sustainable Development Goals (SDGs), making MICS a key resource for development agendas and assessing both national progress and women’s well-being (UNICEF 2024).

IPUMS MICS is an Integrated Public Use Microdata Series project worth checking out for your next demographic research project.

References

Bolgrien, Anna, Elizabeth Heger Boyle, Matthew Sobek and Miriam King. 2024. IPUMS MICS Data Harmonization Code Version 1.1 [Stata Syntax]. IPUMS: Minneapolis, MN https://doi.org/10.18128/D082.V1.1.

National Institute of Statistics and Censuses and UNICEF. 2018. Costa Rica Multiple Indicator Cluster Survey 2011, 2018 [Dataset]. San José, Costa Rica: https://mics.unicef.org/.

UNICEF. 2019. MICS6 Tools. https://mics.unicef.org/tools#survey-design.

UNICEF. 2024. Multiple Indicator Cluster Surveys. https://mics.unicef.org/.

About the Cantril Ladder

Before we can discuss the so-called1 “Cantril ladder,” a modern-day, survey item commonly used in population health surveys to measure evaluative well-being, we need to put it in context.

Well-being is a broad, multidimensional construct, increasingly of interest to those involved with setting national policy agendas and measuring progress towards national development goals.

And for those countries not actively measuring and seeking to improve the well-being of their people, along with other development goals through national policy priorities and resource allocation, that inertia is inconsistent with the unanimous ratification by all 193 member states of the United Nations in adopting the 2030 Agenda for Sustainable Development.

As in the Executive Summary of the latest Sustainable Development Report, “…the SDGs are still achievable. None of their objectives are beyond our reach. The world is off track, but that is all the more reason to double down on the SDGs” (Sachs et al. 2023: vi).

Some national governments have constructed multidimensional well-being frameworks similar to the OECD Framework as shown in the following image (OECD 2020:19).

Others have constructed well-being frameworks more particular to the values and culture of their population, such as the Gross National Happiness index in Bhutan (Ura, Alkire and Zangmo 2012; Verma and Ura 2022), which draws upon Amartya Sen’s capability approach.

The OECD Well-Being Framework, from "How's Life? 2020: Measuring Well-Being" OECD Publishing
This is the OECD Well-Being Framework © OECD Publishing. Used with permission. Citation: OECD (2020), How’s Life? 2020: Measuring Well-being, OECD Publishing, Paris, https://doi.org/10.1787/9870c393-en.

These important well-being data about how the people of the world are doing are being applied at several different stages of the policy cycle, from agenda setting and identifying goals through formulation, implementation monitoring, and ex-post evaluations (Exton and Shinwell 2018:4).

The outcome of interest in the present research is a part of subjective well-being (SWB), which is a dimension of well-being that is about experiencing good mental states and how people assess their own lives. In 1974, the journal Social Indicators Research was founded, and SWB was already a keyword, having been a quality-of-life indicator since the 1950s (Payne 1951/2014).

Regarding conceptualization, there are separate components within SWB: positive and negative affect, and a cognitive appraisal of life (OECD 2013:29). This is where the Cantril ladder comes in, as one common, established way of measuring evaluative well-being or life evaluation.

There are two common SWB indicators. The first SWB indicator is negative affect balance and this indicator reflects the share of the population with more negative feelings than positive feelings on the previous day (OECD 2020:146).

The second SWB indicator is life evaluation, and this indicator reflects the average of the population’s life evaluation on a 0-10 scale. The OECD Guidelines on Measuring Subjective Well-Being (OECD 2013) list the two acceptable survey items when including a single-item evaluative well-being measure.

Both questions have been used in large-scale surveys across many different years, countries, and cultures. Survey administrators need only choose one. They are:

The “satisfaction with life” item:

All things considered, how satisfied are you with your life as a whole these days? Using this card on which 0 means you are “completely dissatisfied” and 10 means you are “completely satisfied” where would you put your satisfaction with life as a whole?

The “Cantril ladder” item:

(Interviewer will first show the picture of the ladder.)
Now, look at this ladder with steps numbered from 0 at the bottom to 10 at the top. Suppose we say that the top of the ladder represents the best possible life for you and the bottom of the ladder represents the worst possible life for you. On which step of the ladder do you feel you stand at this time?

Cantril ladder
This is the Cantril ladder image from the women’s MICS surveys, designed by UNICEF, administered by partners in country such as INEC in CR. It shows a vertical ladder with 0 on the bottom for “worst possible life” and 10 on top for “best possible life”.

Why Use the Cantril Ladder Item

This Cantril ladder survey item is the outcome measure used in the current research. It was chosen here for comparability and consistency with the extant literature, and with the 2030 Agenda for Sustainable Development and the corresponding data initiatives underway across the globe to measure countries’ progress.

Good Health and Well-Being SDG 3
This is the 2030 Agenda for Sustainable Development graphic for goal 3: Good Health and Well-Being. Used with permission.

Sustainable development goal #3 (Ensure healthy lives and promote well-being for all at all ages) and target 3.4 (Reduce by one third premature mortality from non-communicable diseases through prevention and treatment and promote mental health and well-being) include the indicator of subjective well-being and, specifically, this single Cantril ladder survey item (Sachs et al. 2023:103).

Many countries had initially made some preliminary progress towards some targets of the 2030 Agenda. Unfortunately, the global pandemic and associated crises, along with extreme weather events amidst ongoing consequences of COVID-19 and numerous, dire military conflicts, have made it so sustainable development agendas are not making forward progress and most have slid backwards.

All had committed to bringing their country in line with the 2030 Agenda and the SDGs by 2030, and some may end up worse than where they began in 2015.

Based on current projections, the gaps between high income counties (HICs) and low income countries (LICs) in particular might be greater in 2030 than when the sustainable development goals were written in 2015 (Sachs et al 2023). From a recent press release of the SDSN: “Some of the indicators that experienced the most significant reversals in progress include subjective wellbeing, access to vaccination, poverty, and unemployment rate” (SDSN 2023).

Readers can read the Sustainable Development Report online. Also on their web app is an interactive map builder, to quickly visualize trends on each of the SDGs. (Visit the Sustainable Development Report Web App)

The reason for using the Cantril ladder item is its well-established place amidst the sustainable development research agenda. While subjective well-being is not in the Global Indicator Framework, it is in the Sustainable Development Report, in the methodology section, as an indicator for target 3.4, and it is the Cantril ladder item that is used (Sachs et al. 2023:103). Thus while acknowledging methodological concerns with the item, I believe that it makes sense for me to use that which is already being used to track countries’ progress towards SDGs. This is not the time to introduce novel outcome measures for SDG targets.

Methodological Concerns with SWB Measures

Some of the issues to be aware of with all subjective well-being measures are: adaptation, shared method variance, and the risk of measurement error (OECD 2018:176).

These challenges arise from the inherent complexity of measuring life evaluations, which are influenced by a multitude of variables including individual personalities, personal values, daily circumstances, comparative benchmarks, and future expectations (Alkire, 2016:621).

One of the primary concerns with SWB measures is adaptation, or adaptive preferences, a concept that refers to the psychological adjustments people make to their aspirations based on their circumstances.

This adaptation can manifest in two ways. In the first way there can be actual adaptation, where individuals genuinely adjust to changes, later returning to a baseline level of well-being (Lucas & Clark, 2006). There is also a possibility of recalibration of expectations, which can misleadingly appear as adaptation. In the latter case, the SWB measure might reflect revised expectations rather than true well-being, potentially masking underlying issues (Sen 1987:45-46).

For example, consider a woman socialized to believe she is not entitled to literacy. She may not express dissatisfaction with her illiteracy, not because she does not value literacy, but because she has adjusted her expectations to fit her perceived social role.

Similarly, individuals in a community experiencing sustained deprivations might report improved SWB after very minor positive changes, a phenomenon reflecting recalibrated expectations (adaptive preferences again) rather than genuine improvements in well-being.

Another methodological issue is shared method variance, which is a concern whenever multiple self-report measures are used in the same survey. This variance can introduce bias, as responses may be influenced by common factors unrelated to the variables of interest, potentially skewing the interpretation of any nonzero relationships between them.

What is sometimes simply noted as “unaccounted for variance”, however, can be the most important thing, especially when the data are from multiply marginalized women.

Additionally, the Cantril ladder may prompt respondents to engage in social comparisons, which introduces another source of potential bias. The interplay of these factors needs to be considered when using SWB measures.

Critics also argue that SWB measures fail to account for a person’s ‘real opportunities’, focusing instead on subjective perceptions that may not accurately reflect objective conditions (Binder 2014:1198). This underscores a broader critique of the normative use of SWB measures in policy-making, which should be approached with an understanding of these limitations.

1 Initially, I referred to the measurement under discussion as the so-called “Cantril ladder” item. This designation was intended to signal a caveat: the version of the survey item employed over the past twenty years lacks significant methodological content that characterized the original Cantril Self-Anchoring Striving Scale (Cantril 1965). Although both use a ladder metaphor and pose the same question, the original scale was administered within the context of a meaningful conversation—a crucial aspect that differentiated its use from the contemporary application. The original methodology of Hadley Cantril’s ladder, therefore, diverges substantially from its current usage.

References

Alkire, Sabina. 2016. “The Capability Approach and Well-Being Measurement for Public Policy.” Pp. 615-44 in The Oxford Handbook of Well-Being and Public Policy, edited by M. D. Adler and M. Fleurbaey. Oxford, UK: Oxford University Press.

Binder, Martin. 2014. “Subjective Well-Being Capabilities: Bridging the Gap between the Capability Approach and Subjective Well-Being Research.” Journal of Happiness Studies 15(5):1197-217. 10.1007/s10902-013-9471-6.

Cantril, Hadley. 1965. The Pattern of Human Concerns. New Brunswick, NJ: Rutgers University Press.

Easterlin, Richard A. 2021. An Economist’s Lessons on Happiness: Farewell Dismal Science! Cham, Switzerland: Springer Nature.

Easterlin, Richard A. 1974. “Does Economic Growth Improve the Human Lot? Some Empirical Evidence.” Pp. 89-125 in Nations and Households in Economic Growth. New York: Academic Press.

Exton, Carrie and Michal Shinwell. 2018. “Policy Use of Well-Being Metrics: Describing Countries’ Experiences.” OECD Statistics Working Paper Series. Paris: OECD Statistics and Data Directorate.

Lucas, Richard E. and Andrew E. Clark. 2006. “Do People Really Adapt to Marriage?”. Journal of Happiness Studies 7(4):405-26. 10.1007/s10902-006-9001-x.

OECD. 2013. OECD Guidelines on Measuring Subjective Well-Being. Paris: OECD Publishing.

OECD. 2018. For Good Measure: Advancing Research on Well-Being Metrics Beyond GDP. Paris: High-Level Group on the Measurement of Economic Performance and Social Progress.

OECD. 2020. How’s Life? 2020: Measuring Well-Being. Paris: OECD Publishing.

Payne, Stanley Le Baron 1951/2014. The Art of Asking Questions: Studies in Public Opinion, 3. Princeton, NJ: Princeton University Press.

Sachs, Jeffrey D., Guillaume Lafortune, Grayson Fuller and Eamon Drumm. 2023. “Implementing the SDG Stimulus. Sustainable Development Report 2023.” Paris: SDSN, Dublin: Dublin University Press.

SDSN. 2023. “World at Risk of Losing a Decade of Progress on the UN Sustainable Development Goals.” Paris.

Sen, Amartya. 1987. The Standard of Living. Cambridge, UK: Cambridge University Press.

Ura, Karma, Sabina Alkire and Tshoki Zangmo. 2012. “Bhutan: Gross National Happiness and the GNH Index.” The Centre for Bhutan Studies.

Verma, Ritu and Karma Ura. 2022. “Gender Differences in Gross National Happiness: Analysis of the First Nationwide Wellbeing Survey in Bhutan.” World Development 150:105714. 10.1016/j.worlddev.2021.105714.

Want to refer to my prelim?

It has been a while since I passed my written and oral preliminary exams. My written prelim is online for anyone who would like to review it.
Suggested Citation:
Sanborne, Erika. (2022). Why World Leaders Should Prioritize the Well-Being of their People. Retrieved from the University of Minnesota Digital Conservancy, https://hdl.handle.net/11299/226179.
decorative book cover
This is a collage of images comprising the cover of my written prelim.

Curious about the dolphin reference?

The dolphin outline has taken on a life of its own, an expression for the kind of top-down processing required of most academic work from elementary grades through the PhD dissertation prospectus.
dolphins swimming with the Autistic PhD logo
Cartoon dolphins are swimming with the Autistic PhD logo.