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Record W1682413908 · doi:10.47678/cjhe.v45i1.184291

The First Cycle of Study: Teaching and Learning at Cross Purposes?

2015· article· en· W1682413908 on OpenAlexaffvenue
Réal Fillion

Bibliographic record

VenueCanadian Journal of Higher Education · 2015
Typearticle
Languageen
FieldArts and Humanities
TopicEpistemology, Ethics, and Metaphysics
Canadian institutionsUniversity of Sudbury
Fundersnot available
KeywordsInstitutionHigher educationStudent engagementPsychologyQuality (philosophy)Work (physics)PedagogyInvestment (military)SociologyPublic relationsMedical educationMathematics educationPolitical scienceSocial scienceEpistemologyLawEngineering

Abstract

fetched live from OpenAlex

The contemporary university has grown to be a fairly complex institution sustained by many competing interests, not all of which are directly concerned with promoting the work of study, broadly conceived. My concern in the following is with the quality of the subjective experience of studying that universities are still meant to provide. By subjective experience I mean the mindful engagement that is study, and my focus is on such study as it is found in undergraduate programs leading to undergraduate degrees. Given the threat of a growing indifference between professors and students concerning their shared engagement in courses offered at the undergraduate level (offered because of professors’ institutional obligations, taken because of students’ degree requirements), I reconsider the subjective investment of mindful engagement that these courses nevertheless represent.

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)0.010
metaresearch head score (Gemma)0.030
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: Empirical · Consensus signal: none
Teacher disagreement score0.022
Threshold uncertainty score0.055

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0100.030
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0080.012
Scholarly communication0.0220.014
Open science0.0020.016
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0170.005

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 head0.055
GPT teacher head0.311
Teacher spread0.256 · 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
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
Published2015
Admission routes2
Has abstractyes

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