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Record W4232172821 · doi:10.32920/ryerson.14636463.v1

Academic Restructuring at Ryerson University: White Paper

2021· preprint· en· W4232172821 on OpenAlexaboutno aff
Maurice Yeates

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldDecision Sciences
TopicResearch, Science, and Academia
Canadian institutionsnot available
Fundersnot available
KeywordsRestructuringCommissionMandateContext (archaeology)Political sciencePlan (archaeology)White paperManagementPublic administrationLibrary scienceSociologyLawComputer scienceHistoryEconomics

Abstract

fetched live from OpenAlex

<p>[Preface]: "On May 6, 2009 the Provost announced the establishment of an Academic Structures Commission to prepare a Report for him on possible reorganization of some parts of the University. The Commission arises from Recommendation 16 in Shaping Our Future: Academic Plan for 2008/13, which was approved by Senate (May, 2008).In the consultations which guided the formation of the plan, it was argued that the academic structure be revisited to ensure the University responds effectively to internal and external pressures arising from recent and expected growth and change. The mandate of the Provost's Academic Structures Commission (PASC) is to prepare a Report on possible reorganizations within the context of current and anticipated teaching and research developments, following an extensive consultation process. The Commission is to explore a range of possibilities with respect to restructuring existing Faculties and establishing new ones. Since becoming a university in 1993, Ryerson has grown in undergraduate student numbers and programs, established a graduate school, and placed greater emphasis on scholarly, research and creative activity.”</p>

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)0.004
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Open science, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.326
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0010.000
Scholarly communication0.0010.001
Open science0.0050.009
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0080.001

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 head0.152
GPT teacher head0.399
Teacher spread0.248 · 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 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
Published2021
Admission routes1
Has abstractyes

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