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Record W3013312566

Canadian higher education student financial aid policies, products and services in Canada

2019· article· en· W3013312566 on OpenAlexfundaboutno aff
Kazi Abdur Rouf

Bibliographic record

VenueIUScholarWorks (Indiana University) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicHigher Education Research Studies
Canadian institutionsnot available
FundersUniversity of TorontoOntario Federation for Cerebral PalsyCanada Millennium Scholarship FoundationU.S. Department of Veterans Affairs
KeywordsFinancial servicesBusinessFinanceHigher educationEconomic growthEconomics
DOInot available

Abstract

fetched live from OpenAlex

Although Canada is a welfare state and it has need-based priority student financial aid support policies in Canada; however, its higher education financial aid service is not universal. Rather its higher education support services have neoliberal policy matrix (public grants and private loan) financial aid services began to take root in most Canadian provinces. Although since 1964, the Canadian financial aid program has provided over $51 billion in Canada Student Loans to more than 5 million Canadians to help them finance their education and equip them to achieve their career aspirations. The average Canadian student debt is $27,000, up from $8,000 in 1990. The Government of Canada changes many of its higher education financial assistance policies, programs, and products; however, the ratios of the grants: loans are still questionable to many students, researchers, and laymen. Therefore, the federal, provincial and institutional grants need of the increased so that grants portion can be higher than 80% than the loan portion.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.006
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.876
Threshold uncertainty score0.902

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0090.001
Scholarly communication0.0060.001
Open science0.0020.001
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0250.003

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 head0.007
GPT teacher head0.259
Teacher spread0.252 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations1
Published2019
Admission routes2
Has abstractyes

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