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Record W7133533492 · doi:10.26108/d0cg-1x86

History education in Nova Scotia : purpose and practice

2005· article· en· W7133533492 on OpenAlexaboutno aff
Alison Jane Arthur

Bibliographic record

VenueAcadiaU-DEV · 2005
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsCurriculumNova scotiaHistory of educationState (computer science)Conceptual historyCurriculum developmentEducation theoryPoint (geometry)

Abstract

fetched live from OpenAlex

The purpose of this thesis is to examine the state of history education in south-western Nova Scotia. The perceived purpose of history education and how purpose is manifested in classroom practice is examined from the perspectives of educational officials, history teachers, and history students through interviews. Purpose is also examined from the point of view of educational theorists and historians. The purpose of history education according to the province is also addressed through a study of curriculum documents. It is concluded that while educational officials and the provincial curricula are very clear about the purpose of teaching history, teachers and in turn, students, are not. Also, teachers do not seem to fully understand the new learning-outcomes based curricula. These factors lead to a devaluation of history education. It is suggested that an enhanced professional development program could improve understanding of the new curricula and history education in general.

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: Other · Consensus signal: none
Teacher disagreement score0.267
Threshold uncertainty score0.538

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.002
Science and technology studies0.0050.004
Scholarly communication0.0040.001
Open science0.0010.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.103
GPT teacher head0.410
Teacher spread0.307 · 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
GenreOther

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
Published2005
Admission routes1
Has abstractyes

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