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Record W7133008789

Curriculum reform in Canada's universities

2002· dissertation· W7133008789 on OpenAlexaboutno aff
Leslie James Ehrlich

Bibliographic record

VenueTSpace · 2002
Typedissertation
Language
FieldSocial Sciences
TopicHigher Education Governance and Development
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumPaceGovernment (linguistics)Argument (complex analysis)Higher educationProcess (computing)
DOInot available

Abstract

fetched live from OpenAlex

This study focuses on curricular reform in Canada's universities during the 1990s. In the chapters that follow I argue that the process of reform has become more utilitarian as institutions gravitate toward applied research and career preparation in response to current economic and labour market conditions. This argument is grounded in the theory of social reproduction, a critical paradigm which links professional activity to the maintenance and enhancement of exchange relations in capitalist societies. I extend this principle by arguing that knowledge itself is increasingly being framed in terms of capitalist development, as the functions of research and teaching in universities are redesigned to produce results and sets of skills that meet the needs of government and industry. Market-oriented reforms occur in three ways: First, provincial governments take an interventionist approach in university affairs by holding institutions accountable to produce knowledge that is relevant to economic development. Second, as public funding has not kept pace with university expenditures, administrators have taken a managerial approach to planning and operation. Third, increasing student demand for professional education has led to a more vocationally oriented curriculum. Analysis of these tendencies is based on the responses of governments, university administration, and students, all of whom are key stakeholders in the process of curricular reform.

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)0.005
metaresearch head score (Gemma)0.012
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 score0.695
Threshold uncertainty score0.806

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.012
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0160.005
Scholarly communication0.0090.001
Open science0.0020.004
Research integrity0.0030.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.017
GPT teacher head0.344
Teacher spread0.326 · 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
Published2002
Admission routes1
Has abstractyes

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