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Record W7098651044

Public Universities Canadian Society for the Study of Higher Education

2016· article· en· W7098651044 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldPharmacology, Toxicology and Pharmaceutics
TopicPlant-based Medicinal Research
Canadian institutionsnot available
Fundersnot available
KeywordsHigher educationCreativityNothingWork (physics)Field (mathematics)Process (computing)
DOInot available

Abstract

fetched live from OpenAlex

To complete in the increasingly competitive marketplace, public universities need to become more flexible and more focused in reactions to expanding and changing demands. As the case study of five European universities by B. Clark (1998) demonstrates, an entrepreneurial response on the part of universities results in diversified income, a decreased dependence on the government, new approaches that provide a different institutional character, and a more focused, confident, and resilient university. The tendencies evidently in and methods and intricacies of this response are discussed in this essay. As public universities seek new administrative forms and strategies to motivate the academic heartland to acquire the entrepreneurial culture that stimulates innovation, self-reliance, and pursuit of discretionary funds, hard work is needed. Doing nothing poses very large risks. The process of transformation in a university is an immense field of creativity and opportunities, but it is a necessity. (Contains 27 references.) (SLD) Reproductions supplied by EDRS are the best that can be made from the original document.

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)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
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 score0.980
Threshold uncertainty score0.890

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0040.008
Science and technology studies0.0060.004
Scholarly communication0.0120.004
Open science0.0020.004
Research integrity0.0040.003
Insufficient payload (model declined to judge)0.4610.177

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 head0.285
GPT teacher head0.483
Teacher spread0.199 · 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.

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
Published2016
Admission routes1
Has abstractyes

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Same topicPlant-based Medicinal ResearchFrench-language works237,207