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Record W4313588246 · doi:10.29173/css39

Piloting Historical Thinking Lessons to Address Climate Change

2022· article· en· W4313588246 on OpenAlex
Heather E. McGregor, Sara Karn, Rebecca S. Evans, Jackson Pind

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

VenueCanadian Social Studies · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsTrent University
Fundersnot available
KeywordsCritical thinkingFeelingEnvironmental educationClimate changeQualitative researchHistorical thinkingSocial studiesPedagogyPsychologySociologyMathematics educationSocial scienceSocial psychologyEcology

Abstract

fetched live from OpenAlex

To demonstrate how the history classroom could become an important site for addressing climate change, this article describes the piloting of three lessons. Our qualitative case study occurred in an elective environmental education course with teacher candidates who participated in the lessons and were invited to provide feedback. We describe the lessons and their development, and share results from surveys and an interview. Participants identified several educational benefits and expressed feeling better prepared to teach both history and critical thinking in general. Our findings suggest that these lessons may serve as useful examples for developing new resources to support educators in teaching climate change alongside critical and historical thinking.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.928
Threshold uncertainty score0.993

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0130.000
Scholarly communication0.0000.000
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 head0.439
GPT teacher head0.447
Teacher spread0.008 · 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