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Record W7111707991

AS-982-24 Resolution on the Proposed 14-Week Trimester Calendar and Year-Round Operations

2024· article· W7111707991 on OpenAlexaboutno aff

Bibliographic record

VenueDigitalCommons - CalPoly (California State Polytechnic University) · 2024
Typearticle
Language
FieldEnvironmental Science
TopicUkraine: War, Education, Health
Canadian institutionsnot available
Fundersnot available
KeywordsTerm (time)Quarter (Canadian coin)Administration (probate law)Academic communityResolution (logic)Spring (device)
DOInot available

Abstract

fetched live from OpenAlex

Resolves that the Academic Senate objects to the proposed 14-week term length, which is presented in the 2026-2027 Academic Calendar, because it implements symmetrical fall, winter, and spring term lengths that modify, without senate consultation and approval, the sixteen-week fall and spring semester term lengths and asymmetrical summer term in AS-942-22; and further resolves that the Academic Senate strongly encourages the administration to postpone the adoption of symmetric trimesters proposed in the 2026-2027 Academic Calendar until Cal Poly has had the opportunity to institute the Quarter to Semester transition as it originally was mandated by the Chancellor’s Office in 2021, with two 15-week Semesters with one week of final exams and a Summer semester; and further resolves that the Academic Senate strongly encourages the administration to postpone implementation of the Year-Round Operations proposal until the integration with Cal Maritime, should it be approved by the CSU Board of Trustees in November 2024, is complete and has been shown to be both financially and functionally sustainable, and the incoming community from Cal Maritime has had an opportunity to provide feedback on the proposal.

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)0.016
metaresearch head score (Gemma)0.028
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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.096
Threshold uncertainty score0.235

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0160.028
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0020.001
Science and technology studies0.0110.003
Scholarly communication0.0150.002
Open science0.0040.004
Research integrity0.0200.018
Insufficient payload (model declined to judge)0.0700.063

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 head0.020
GPT teacher head0.233
Teacher spread0.213 · 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
Published2024
Admission routes1
Has abstractyes

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Same venueDigitalCommons - CalPoly (California State Polytechnic University)Same topicUkraine: War, Education, HealthFrench-language works237,207