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Record W7126156780 · doi:10.26443/mje/rsem.v59i3.10086

Montreal Jewish Day School teachers’ real-time experiences during Covid-19 online distance learning

2025· article· en· W7126156780 on OpenAlexaffvenueabout
Lauren Thurber, Sivane Hirsch, Devorah Feldman

Bibliographic record

VenueMcGill Journal of Education / Revue des sciences de l éducation de McGill · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicJewish Identity and Society
Canadian institutionsUniversité LavalMcGill University
Fundersnot available
KeywordsTimelineDisappointmentDistance educationJudaismFeelingOnline discussionIdentity (music)Community of practice

Abstract

fetched live from OpenAlex

During the Covid-19 pandemic, Montreal Jewish Day Schools shifted to online distance learning. This study follows eight elementary and high school teachers in real-time through observations and group interviews. Applying a Community of Inquiry framework, we unpack the social, conceptual, and pedagogical elements of this pedagogical shift to understand its three “modes”: survival, transition, and innovation, distinguished by stability and connectivity. Peer-to-peer and student-teacher connectivity was mostly underdeveloped and fostered feelings of disappointment and frustration. Teachers varied in their engagement with specific Judaic traditions within their online classrooms and relied on school-wide resources to sustain Jewish identity connectivity for students. The ever-changing timeline of the shifts in conjunction with personally- and community- attributed pressures contributed to teachers’ experiences of anxiety.

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)0.002
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.549
Threshold uncertainty score0.897

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0100.005
Scholarly communication0.0030.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.150
GPT teacher head0.424
Teacher spread0.274 · 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 designQualitative
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
Published2025
Admission routes3
Has abstractyes

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