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Record W4362475865 · doi:10.24908/iqurcp16330

Addressing Financial Barriers to Higher-Education

2023· article· en· W4362475865 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueInquiry Queen s Undergraduate Research Conference Proceedings · 2023
Typearticle
Languageen
FieldAgricultural and Biological Sciences
TopicAgricultural and Financial Auditing
Canadian institutionsQueen's University
Fundersnot available
KeywordsScholarshipStudent debtDebtHigher educationCurriculumFinanceWork (physics)Public relationsBusinessPolitical scienceEconomicsEconomic growthEngineering

Abstract

fetched live from OpenAlex

Many students choose not to pursue higher education due to its financial burden and the looming threat of debt that follows. However, 10 million dollars of scholarship money in Canada goes unclaimed each year due to a lack of applicants (Griffiths, 2022). Students who require financial assistance for higher education can only capitalize on the available scholarship money if they have the necessary skills to create successful applications (Hoff, 2013). Furthermore, the low-income students who will benefit the most from access to these resources often have to work part-time jobs after school, so they are unable to devote the necessary time to this process (Singh,1998). To address this barrier, we have developed an equitable, accessible module-based program that strives to connect the surplus of untapped scholarship money each year with students who desire to fund their pursuit of higher education. These modules will facilitate equitable access to higher education by fostering students' skills related to budgeting, financial planning, scholarship searching, and application writing and will be implemented directly in the high school curriculum. To facilitate their implementation and avoid any potential pitfalls, the modules would decrease the burden on educators, be accessible to students with disabilities, and include content-related to cybersecurity. By helping foster students' self-efficacy and confidence in their knowledge and skills so they can apply for funding, we aim to increase the number of people applying for scholarships so that financial resources are no longer a significant barrier to higher education. References Griffiths, A. (2022, January 8). Canadian scholarships by province. GrantMe.https://grantme.ca/canadian-scholarships-by-province/ Hoff, E. (2013). Interpreting the early language trajectories of children from low-SES and language minority homes: Implications for closing achievement gaps. Developmental Psychology, 49(1), 4–14. https://doi.org/10.1037/a0027238 Singh, K. (1998). Part-Time Employment in High School and Its Effect on Academic Achievement. The Journal of Educational Research, 91(3), 131–139. https://doi.org/10.1080/00220679809597533

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.

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)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.331
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.004
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.001

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 head0.204
GPT teacher head0.374
Teacher spread0.170 · 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