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Record W7120821990

Educação superior e a eficácia dos mecanismos de financiamento das políticas públicas no Canadá

2018· article· pt· W7120821990 on OpenAlexaboutno aff
Danilo de Melo Costa

Bibliographic record

VenueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas) · 2018
Typearticle
Languagept
FieldSocial Sciences
TopicEducation and Public Policy
Canadian institutionsnot available
Fundersnot available
KeywordsContext (archaeology)PropositionPublic policyExploratory researchExploratory analysisHigher educationPublic sector
DOInot available

Abstract

fetched live from OpenAlex

This research analyzes the effectiveness of public policy funding mechanisms for higher education in Canada in the period from 2003 to 2012, assuming a gap to be explored concerning the proposition of new public policies that contribute to financing higher education worldwide. When it comes to the methodological procedures, this study was designed as exploratory and quantitative. A group of public policies were statistically analyzed, using as a reference the compound annual growth rate (CAGR), which was in turn based on the investments made and the number of students attended in the period. The results showed that Canada has proven to be a country of solid and well-defined public policies, which had an impact on its good performance, with an emphasis on: the CESG policy, which presents the proactive way to ensure access to, and presence of, young people in higher education; CSGP/CSLP, which was statistically significant in relation to the percentage of students attended; and OSAP / Reaching Higher policy, which was more sensitive to the needs of the context in which it is inserted (Ontario province).

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)0.006
metaresearch head score (Gemma)0.019
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.904
Threshold uncertainty score0.695

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0060.019
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0030.003
Science and technology studies0.0040.003
Scholarly communication0.0080.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0050.000

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 head0.033
GPT teacher head0.319
Teacher spread0.286 · 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
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".

Quick stats

Citations0
Published2018
Admission routes1
Has abstractyes

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Same venueLA Referencia (Red Federada de Repositorios Institucionales de Publicaciones Científicas)Same topicEducation and Public PolicyFrench-language works237,207