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Record W3197690545 · doi:10.14288/1.0392736

Exploring the dynamics of “Affordability” for students at UBC Vancouver

2020· article· en· W3197690545 on OpenAlexaffabout
Stephanie Lin, Joy Jiao, Emma Gangbar

Bibliographic record

VenuecIRcle (University of British Columbia) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Learning Practices
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsDynamics (music)Mathematics educationRegional scienceGeographySociologyPsychologyPedagogy

Abstract

fetched live from OpenAlex

“School is already so expensive … I would hope you can understand you are targeting one of the least financially stable demographics … it's students’ whole lives you’re impacting” (The University of British Columbia, 2018). This personal anecdote by a UBC student in the UBC Board of Governors Tuition Consultation Report encapsulates the deep feelings of the vexation of the all-consuming impact of a school-wide tuition increase. Affordability can be defined as a cost within one’s financial means, or the cost relative to the amount that the purchaser is able to pay (Das, 2017). However, this rather limited definition must be expanded upon and wholly understood. Affordability has been an ongoing, complex discussion at UBC, in Vancouver, Canada, and around the globe (Das, 2017; The University of British Columbia, 2018). It affects individuals to varying degrees and has the potential to control all aspects of one’s life (Das, 2017). However, the issue of affordability is often considered narrowly by primarily focusing on income, rather than in conjunction with the affordability of food, education, finances, and other related factors (Das, 2017). This multidimensionality of affordability has yet to be synthesized. Therefore, from the point of view of a UBC student to the broader contextual issues of Vancouver and North America, the purpose of this project was to bring to light the layers of affordability, with a particular focus on the affordability of food. In this sense, the goal of this study was to collect a wealth of nuanced knowledge regarding affordability from a post-secondary student’s viewpoint using a mixed method of data collection approach. The following objectives were used to accomplish this goal - identify affordability related policies in Canada and relate this to current campus policy, gain a thorough understanding of the affordability experience of UBC students, comprehend the status of affordability on campus from a student perspective and its implications, and outline a set of thorough action and research-based recommendations to create a more affordable campus. Applying Community Based Action Research (CBAR) as our methodological framework, we collected research from both primary and secondary sources. Following the principles of CBAR, we ensured that all stakeholders throughout the research process were involved (Burns et al., 2011). With our SEEDS client and our team of three students, we agreed that the multiplex issue of affordability is best understood and untangled based on UBC student narratives. Primary sources of data emerged from the diverse student body - commuters and noncommuters, domestic and international, undergraduate and graduate, and across a variety of faculties, and living arrangements. Using a random sampling technique, this exploration took place on campus through five pilot semistructured interviews and an additional 21 semi-structured interviews, totaling twenty-six in order to hear from the voices of the students themselves. To complement the students’ personal anecdotes, secondary literature research involved delving into affordability policy at UBC and other Canadian post-secondary institutions, the affordability of higher education outside of Canada, and the intersectionality of affordability. Using these two forms of data collection, we could better comprehend the status of affordability on campus in comparison to other highereducation institutions as well as its extensive impact on a student’s everyday life. From this semester-long endeavour, we were able to understand and encompass the UBC student perspective and challenges related to affordability that complemented the secondary research. Key findings included that most students interviewed tracked their spending mentally, which has proved to be an ineffective technique. Also, oftentimes students were forced to make sacrifices to afford their fixed costs, such as eating at restaurants less frequently. Finally, most students interviewed were regularly skipping meals largely due to lack of time, not lack of money. Based on these findings, we produced a set of recommendations that cohesively support each other with a systems-understanding of affordability from both UBC students as well as Canadian and American secondary-research. Action-based recommendations include creating a UBC-wide financial literacy week, as well as UBC Food Services subsidized grocery store, restaurant, and convenience food items on campus. Research-based recommendations include app development to save students money on food costs, investigating self-preparation food facilities, and reducing the cost of all items sold at UBC Food Service outlets. We believe that these proposed recommendations can be applied to UBC to address affordability on campus, and to other postsecondary institutions. In doing so, we hope to help achieve the goal of a more affordable university experience, with an emphasis on food affordability. Disclaimer: “UBC SEEDS provides students with the opportunity to share the findings of their studies, as well as their opinions, conclusions and recommendations with the UBC community. The reader should bear in mind that this is a student project/report and is not an official document of UBC. Furthermore readers should bear in mind that these reports may not reflect the current status of activities at UBC. We urge you to contact the research persons mentioned in a report or the SEEDS Coordinator about the current status of the subject matter of a project/report.”

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.665
Threshold uncertainty score0.892

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

Machine scores (provisional)

The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.

Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.

Opus teacher head0.053
GPT teacher head0.280
Teacher spread0.227 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designObservational
Domainnot available
GenreEmpirical

How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".

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Citations0
Published2020
Admission routes2
Has abstractyes

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