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Record W4285676798 · doi:10.29173/crossings95

Educating the Electorate

2022· article· en· W4285676798 on OpenAlexaffabout
Emma Jones

Bibliographic record

VenueCrossings An Undergraduate Arts Journal · 2022
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsCurriculumCitizenship educationCitizenshipSocial studiesContent (measure theory)IndigenousPedagogySociologyCritical theoryDemocracyRace (biology)Political scienceSocial scienceGender studiesLawPolitics

Abstract

fetched live from OpenAlex

Social Studies education is politicized, powerful, and highly contentious. Scholars have long debated about the content of Social Studies curricula, interest groups have historically tried to influence its material, and in recent years headlines have highlighted controversial subjects like Critical Race Theory and Indigenous reconciliation. This paper argues that it is impossible to teach a neutral Social Studies curriculum, and so it is essential that educators are mindful of the impact their content will have on young minds and future citizens of their society. This paper first breaks down Canadian Social Studies curricula into their two main components: history and citizenship. The paper then provides an examination of how various models of citizenship impact the way history is taught, and demonstrates the impact those models of citizenship have on how students feel about their society and the role they play within it. These models have implications for not only the content of classrooms but for the future of democracy 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)0.003
metaresearch head score (Gemma)0.006
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: Empirical · Consensus signal: none
Teacher disagreement score0.135
Threshold uncertainty score0.269

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0110.005
Scholarly communication0.0050.002
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0150.003

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 head0.131
GPT teacher head0.407
Teacher spread0.276 · 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
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
Published2022
Admission routes2
Has abstractyes

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Same venueCrossings An Undergraduate Arts JournalSame topicEducator Training and Historical PedagogyFrench-language works237,207