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Record W2782598014

A Call for Teacher Professional Learning and the Study of Religion in Social Studies

2017· article· en· W2782598014 on OpenAlexaffvenueabout
Margaretta L. Patrick, Vanessa Gulayets, Carla L. Peck

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicReligious Education and Schools
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCitizenshipPedagogyProfessional developmentProfessional learning communitySociologyReligious educationFaculty developmentPublic relationsPolitical scienceLaw
DOInot available

Abstract

fetched live from OpenAlex

Religion is important to study in social studies because many religious iReligion is important to study in social studies because many religious individuals, groups, and movements engage with public issues and because countries are increasingly religiously diverse. In response, scholars are promoting education about religion in citizenship education. However, there remain few programs about religion in Canadian public schools and even less research about them. This article begins to address the gap by proposing three priorities for teacher professional learning and the study of religion for social studies teachers. The priorities are drawn from interviews with Alberta teachers, whose beliefs about religion in the classroom can be divided into three categories identified by the authors as nominal, attentive, and integrated. If many teachers fall into one of these categories, then the professional learning priorities suggested here have wide-ranging application.

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)0.132
metaresearch head score (Gemma)0.099
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: Commentary · Consensus signal: Commentary
Teacher disagreement score0.132
Threshold uncertainty score0.698

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.1320.099
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0030.002
Bibliometrics0.0060.004
Science and technology studies0.0340.127
Scholarly communication0.0300.032
Open science0.0060.025
Research integrity0.0310.041
Insufficient payload (model declined to judge)0.0090.002

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 head0.082
GPT teacher head0.404
Teacher spread0.322 · 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
GenreCommentary

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

Citations11
Published2017
Admission routes3
Has abstractyes

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