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Record W7006336231

Teaching and Learning for Historical Justice: A Comparative Case Study of Four Sites of History Education in Canada

2021· dissertation· W7006336231 on OpenAlexaboutno aff

Bibliographic record

VenueTSpace · 2021
Typedissertation
Language
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
FundersOffice of International Science and Engineering
KeywordsRedressCurriculumInjusticeSocial history (medicine)ColonialismComparative historical researchSocial studiesEconomic Justice
DOInot available

Abstract

fetched live from OpenAlex

Recently, Canadian governments and public institutions have initiated a wide range of symbolic gestures and policy reforms aimed at reconciling historical injustices. Reforming history education to teach Canada’s difficult past has been a key priority in this movement, leading to curricular changes and the development of new resources across the country. This dissertation explores four case studies that consider history education’s role in making sense of past injustice and pursuing historical justice and redress in Canada. The four case studies include a curriculum reform process in British Columbia, two grade 9 social studies classrooms engaging with the difficult past, a university field school and bus tour, and a temporary exhibit at the Royal Ontario Museum focused on a difficult history. Drawing on theories of settler colonialism, multidirectional memory, and historical consciousness, this comparative case study illustrates the relationship between teaching and learning difficult history amid a culture of redress in Canada. This dissertation argues that history education’s new roles and responsibilities for helping to right historical wrongs present specific challenges and opportunities for teachers and learners. In particular, this dissertation argues that issues of identity, group memory, and collective responsibility are all brought into focus when educators and learners engage the difficult past. This dissertation raises questions and makes suggestions about the possible roles and limitations for social studies and history education in pursuit of reconciliation and redress in post-conflict and settler colonial contexts.

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)0.008
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 score0.102
Threshold uncertainty score0.740

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.008
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.006
Science and technology studies0.0720.015
Scholarly communication0.0080.003
Open science0.0050.008
Research integrity0.0040.006
Insufficient payload (model declined to judge)0.0060.001

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 head0.171
GPT teacher head0.461
Teacher spread0.290 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

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