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Record W7162129543 · doi:10.82308/36818

Tenure and promotion evaluations: academics' perceptions at Canadian universities' faculties of education

2017· dissertation· en· W7162129543 on OpenAlexaboutno aff
Saturnin Espoir Ntamba Ndandala

Bibliographic record

Venuenot available
Typedissertation
Languageen
FieldSocial Sciences
TopicEvaluation of Teaching Practices
Canadian institutionsnot available
Fundersnot available
KeywordsPromotion (chess)PerceptionEquity (law)Higher educationAmbiguityFunction (biology)

Abstract

fetched live from OpenAlex

Up to now, existing studies suggest that there is a dearth of literature on faculty perceptions about performance evaluations, in particular for education professors. Through mixed methods and equity theory of management, the present study identifies the perceptions of education professors about performance evaluations at Canadian universities' education faculties. It outlines which performance appraisals related to tenure and promotion processes across Canadian universities' education faculties function as workplace demotivators. Based on interview and survey findings, this study reveals that education professors are frustrated with the ambiguity of departmental appraisal standards and merit expectations, and the procedural shortcomings of student course evaluations and peer ratings. However, their dissatisfaction with the aforesaid issues does not translate into turnover intentions. On the contrary, education professors from both professorial groups (junior and senior) and sex (male and female) hold retention intentions.

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)0.008
metaresearch head score (Gemma)0.022
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Evaluation · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.992
Threshold uncertainty score0.489

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0080.022
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.004
Science and technology studies0.0070.003
Scholarly communication0.0050.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.143
GPT teacher head0.498
Teacher spread0.354 · 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 designQualitative
DomainEvaluation
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
Published2017
Admission routes1
Has abstractyes

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