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Record W1593186032

The Making of a Policy Regime: Canada's Post-Secondary Student Finance System Since 1994

2012· article· en· W1593186032 on OpenAlexaboutno aff
Richard Wellen, Paul Axelrod, Roopa Desai-Trilokekar, Theresa Shanahan

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Policy and Reform Studies
Canadian institutionsnot available
Fundersnot available
KeywordsStudent debtGovernment (linguistics)Student loanPolicy analysisDebtPublic administrationEducation policyEconomicsLoanPolitical scienceHigher educationHigher education policyFinancePublic economicsEconomic growth
DOInot available

Abstract

fetched live from OpenAlex

This paper examines the pattern of decision-making, lobbying, and influence that led to the landmark series of federal student assistance policies introduced by Jean Chrétien’s Liberal government in the late 1990s. The package of new initiatives—dubbed the Canada Opportunities Strategy—not only partially re-versed an earlier period of fiscal restraint but also brought a new emphasis on direct forms of student assistance such as grants, bursaries, and tax credits. However, programs such as the Canada Millennium Bursaries and the Cana-da Education Savings Grants, despite their focused approach and innovative structure, came to be regarded as weak policy tools when measured against their ostensible goals of widening access to post-secondary education and effi-ciently targeting student assistance on the basis of need. The new policy regime also failed to fulfil nearly two decades of previous efforts by policy-makers to transform Canada’s student debt program into a systematic income-contin-gent loan program. We offer explanations of this pattern of policy inconsis-tency and incoherence by examining the awkward challenges of intergovern-mental relations in the Canadian federal system as well as the fragmentation and competing goals now evident in student assistance policy networks. We contrast the student finance policy regime with the arguably more coherent set of research and innovation policies established by the federal government dur-ing the same period. We use policy network analysis as our theoretical frame-work, and we use data from our extensive interviews with higher education stakeholders and policy-makers to provide empirical support.

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 categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score1.000

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 communication0.0000.000
Open science0.0000.000
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 head0.016
GPT teacher head0.329
Teacher spread0.313 · 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.

Study designTheoretical or conceptual
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

Citations6
Published2012
Admission routes1
Has abstractyes

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