MétaCan
Menu
Back to cohort
Record W2605211024

Introduction: Historical thinking, historical consciousness

2017· article· en· W2605211024 on OpenAlexvenueaboutno aff
Lorna R. McLean, Sharon Anne Cook, Stéphane Lévesque, Timothy J. Stanley, Pamela Rogers, Jamilee Baroud

Bibliographic record

VenueCanadian Journal of Education / Revue canadienne de l éducation · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsHistorical thinkingPublic historyConsciousnessPoliticsSociologyPolitical consciousnessMedia studiesSocial sciencePedagogyHistoryPolitical sciencePsychologyLaw
DOInot available

Abstract

fetched live from OpenAlex

In September, 2014, the University of Ottawa Education Research Unit, Making History / Faire l’histoire , hosted Canadian History at the Crossroads , a SSHRC-funded symposium in collaboration with the Canadian Museum of History in Gatineau, Quebec. The symposium brought together multiple stakeholders, historians, history and museum educators, classroom teachers—including Governor General’s award winners as well as teacher education and graduate students—to stimulate further public dialogue on pedagogies of history and the politics of remembrance. Building on some of the symposium’s original contributions as well as other submissions, this Canadian Journal of Education Special Capsule advances current debates in history education, historical thinking, and historical consciousness, and forges new directions for collective understandings of the past, by connecting with everyday lived experiences in the present. The contributions range from discussions of how young people themselves understand their past to the link- ages between forms of remembering and conceptions of the nation itself.

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)0.001
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Editorial · Consensus signal: none
Teacher disagreement score0.147
Threshold uncertainty score0.293

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0070.014
Scholarly communication0.0080.005
Open science0.0010.002
Research integrity0.0030.005
Insufficient payload (model declined to judge)0.0290.004

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 head0.105
GPT teacher head0.342
Teacher spread0.237 · 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 designTheoretical or conceptual
Domainnot available
GenreEditorial

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

Citations1
Published2017
Admission routes2
Has abstractyes

Explore more

Same venueCanadian Journal of Education / Revue canadienne de l éducationSame topicEducator Training and Historical PedagogyFrench-language works237,207