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Record W6989954390

The citizen self and aboriginal “other” : notions of citizenship and aboriginality in British Columbian social studies education, 1945-present

2013· article· en· W6989954390 on OpenAlexaboutno aff

Bibliographic record

VenueArca (British Columbia Electronic Library Network) · 2013
Typearticle
Languageen
FieldSocial Sciences
TopicEducator Training and Historical Pedagogy
Canadian institutionsnot available
Fundersnot available
KeywordsNucleofectionGestational periodHyporeflexiaPretextTSG101DiafiltrationProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Social studies education in British Columbia from the 1940s until present has upheld active citizenship as a central objective of the program. While citizenship is never clearly defined, generally it has been assumed that through a process of self-actualization students come to know their rights and responsibilities as Canadian citizens. Problematically, these notions of citizenship have shaped the narration of Aboriginality within social studies education. Aboriginality has been represented in learning outcomes and resources materials within a progressive Canadian metanarrative, creating inaccurate and uninformed characterizations of Aboriginal peoples. Overall, social studies education has had a negative impact on the First Nations-Canadian relationship. However, social studies education could assist in developing more positive relationships. Engaging students in transformed historical study that fosters questioning, examines narrative choices, sees negotiation and interaction, recognizes and honours difference, and allows for dialogue, may foster more promising relationships in the future.

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)0.003
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 score0.069
Threshold uncertainty score0.502

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.003
Science and technology studies0.0380.040
Scholarly communication0.0100.003
Open science0.0010.006
Research integrity0.0010.004
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 head0.021
GPT teacher head0.308
Teacher spread0.287 · 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
Published2013
Admission routes1
Has abstractyes

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