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Record W4387092957 · doi:10.7202/1106306ar

Demoralization as a form of teacher burnout

2023· article· en· W4387092957 on OpenAlex
Laura Sokal, Lesley Eblie Trudel

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
venuePublished in a venue whose home country is Canada.

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicTeacher Professional Development and Motivation
Canadian institutionsUniversity of Winnipeg
Fundersnot available
KeywordsBurnoutDepersonalizationAttritionPsychologyEmotional exhaustionArgument (complex analysis)Social psychologyPhenomenonClinical psychologyMedicineEpistemologyPhilosophy

Abstract

fetched live from OpenAlex

<p>Over fifty years of research investigating teacher burnout has resulted in a well-accepted model of burnout that involves three dimensions: exhaustion, depersonalization, and loss of accomplishment. Recently, a new cause of teacher attrition has been proposed called “demoralization,” on the argument that demoralization is a distinct phenomenon from burnout. In light of new research methodologies that allow for examination of unique pathways or “profiles” of teacher burnout, we explore the question, providing an analysis that suggests instead that depersonalization can be fairly represented as one profile of burnout.</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.

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)0.005
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0050.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.374
GPT teacher head0.472
Teacher spread0.098 · 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