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Record W2033739705 · doi:10.1787/hemp-24-5k9bdtj6b0r6

Strategic planning for academic research

2012· article· en· W2033739705 on OpenAlexaffabout
Creso M. Sá, Merli Tamtik

Bibliographic record

VenueHigher Education Management · 2012
Typearticle
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsUniversity of Toronto
Fundersnot available
KeywordsStrategic planningScope (computer science)Institutional researchHigher educationAdministration (probate law)Public relationsStrategic human resource planningEmpirical researchSociologyPolitical scienceManagementBusinessMarketingEconomicsComputer science

Abstract

fetched live from OpenAlex

This paper reports on an empirical study of research planning in Canadian universities. Drawing on data compiled during interviews with senior administrators from 27 academic units in 10 universities, the paper analyses how strategic planning has been applied to the research mission over the past decade. Findings reveal variability in processes and attitudes about planning, while suggesting that the scope of planning activities in most cases has been somewhat narrow and short-term. The implications of these findings for the administration of research are discussed.

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)0.045
metaresearch head score (Gemma)0.048
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Incentives · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.955
Threshold uncertainty score0.282

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0450.048
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0050.010
Science and technology studies0.0120.027
Scholarly communication0.0290.012
Open science0.0020.011
Research integrity0.0060.007
Insufficient payload (model declined to judge)0.0120.003

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 head0.682
GPT teacher head0.624
Teacher spread0.058 · 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 designTheoretical or conceptual
DomainIncentives
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

Citations5
Published2012
Admission routes2
Has abstractyes

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