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Record W4391864980 · doi:10.51644/9781554581160

Collective Autonomy

2006· book· en· W4391864980 on OpenAlexaboutno aff
Edward J. Monahan

Bibliographic record

Venuenot available
Typebook
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsAutonomyPolitical scienceSociologyLaw

Abstract

fetched live from OpenAlex

Chronicles the rise and decline of Ontario universities from the halcyon 1960s to the Common Sense Revolution through the history of its planning association, the Council of Ontario Universities. Collective Autonomy: A History of the Council of Ontario Universities, 1962-2000 is the first full-length account of an organization that has played a major role in the development of the university system in Ontario. Edward J. Monahan served as the council’s chief executive officer for over fifteen years. This is his insider’s account, enhanced by archival material, of the key role the universities played in planning the high academic quality of the Ontario provincial university system. Collective Autonomy traces the evolution of Ontario universities over a period of forty years, from the halcyon days of the 1960s, during which massive injections of public funds transformed these institutions from ivory towers to public utilities, through the 1970s and ’80s when universities were downgraded as a government spending priority and problems began to develop. It concludes by looking at the problems created by the “Common Sense Revolution” and the resulting severe cutbacks in government grants to universities. It chronicles the efforts of the universities to preserve their autonomy while expanding their service to the common good, and their efforts to maintain the delicate balance between university autonomy and public accountability.

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)0.001
metaresearch head score (Gemma)0.001
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: Other · Consensus signal: Other
Teacher disagreement score0.094
Threshold uncertainty score0.683

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0180.019
Scholarly communication0.0050.003
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0100.001

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 head0.009
GPT teacher head0.210
Teacher spread0.201 · 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

Citations0
Published2006
Admission routes1
Has abstractyes

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