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Record W4399839979 · doi:10.55016/ojs/ajer.v48i4.54946

Silent Voices, Silent Stories: Japanese Canadians in Social Studies Textbooks

2002· article· en· W4399839979 on OpenAlexaffvenueabout
Jennifer Tupper

Bibliographic record

VenueAlberta Journal of Educational Research · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsUniversity of Alberta
Fundersnot available
KeywordsPsychologySociologySocial psychologyGender studies

Abstract

fetched live from OpenAlex

The purpose of this article is to illustrate the importance of reading social studies textbooks through a critical lens. Students and teachers who engage in critical interrogation of texts will broaden their understanding of history and the inequities that have shaped Canadian society over time. Informed by both critical and postmodern theory, this analysis of three commonly used grade 10 social studies textbooks elucidates the limitations inherent in each textbook's discussion of the history of Japanese Canadians. It also illustrates the failure to contextualize specific events in history, potentially leaving students with a narrow conception of historical events. Historical sources written by Japanese Canadians were used to gain a better understanding of their experiences and to strengthen the analysis. The implications of the limitations for students and teachers are discussed, as well as how textbooks can be used more productively in social studies classrooms.

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)0.009
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 score0.187
Threshold uncertainty score0.377

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.009
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0280.014
Scholarly communication0.0080.003
Open science0.0020.006
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0040.000

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 head0.381
GPT teacher head0.512
Teacher spread0.131 · 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

Citations10
Published2002
Admission routes3
Has abstractyes

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