MétaCan
Menu
Back to cohort
Record W1761531544 · doi:10.47678/cjhe.v42i1.1900

Une enquête sur l’éthique professionnelle des enseignants du collégial québécois : caractéristiques, points de repère et stratégies utilisés pour traiter de préoccupations éthiques

2012· article· en· W1761531544 on OpenAlexaffvenueabout
Luc Desautels, Christiane Gohier, Jacques Joly, France Jutras, Jean Gabin Ntebutse

Bibliographic record

VenueCanadian Journal of Higher Education · 2012
Typearticle
Languageen
FieldSocial Sciences
TopicSociety, Economy, and Ethics Research
Canadian institutionsCegep regional de Lanaudiere
Fundersnot available
KeywordsNormativeConscienceSociologyPedagogyPsychologyPolitical scienceLaw

Abstract

fetched live from OpenAlex

Some results of a survey on professional ethics conducted among francophone college teachers in Quebec are compared with a review of the literature and the results of focus groups previously held on the subject. The justification reasons behind the ethical nature of certain professional concerns, along with the guidelines and the resolution strategies used to address those concerns, are found to be similar. These justifications relate primarily to situations where there is a conflict of conscience, a conflict of values or consequences on others, particularly students; the calling into question of professional integrity stands out as a particular justification not mentioned in earlier studies. The guidelines to deal with dilemmas are also similar: institutional normative texts and values deemed relevant by the teachers come first. The results show a good balance between the use of these two types of guidelines (external and internal) by teachers. The main strategies applied by teachers for resolving dilemmas are peer discussions and personal reflection.

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)0.011
metaresearch head score (Gemma)0.026
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score0.320

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.026
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0120.008
Scholarly communication0.0060.003
Open science0.0010.002
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.0050.000

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 head0.080
GPT teacher head0.377
Teacher spread0.298 · 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 designObservational
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

Citations7
Published2012
Admission routes3
Has abstractyes

Explore more

Same venueCanadian Journal of Higher EducationSame topicSociety, Economy, and Ethics ResearchFrench-language works237,207