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Record W1953190000

Integrating Aboriginal Perspectives in Education: Perceptions of Pre-Service Teachers

2013· article· en· W1953190000 on OpenAlexaff
Frank Deer

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsApprehensionPerceptionMainstreamTeacher educationQualitative researchPedagogyPsychologyPrincipal (computer security)Semi-structured interviewMedical educationSociologyMedicineSocial sciencePolitical science
DOInot available

Abstract

fetched live from OpenAlex

This study explored teacher candidates ’ perceptions of the potentialities and challenges associated with the integration of Aboriginal perspectives into mainstream education. Participants in this study were 2nd-year teacher candidates of a two-year teacher education programme who have completed a course on Aboriginal education. Using a qualitative approach, the principal investigator conducted interviews with teacher candidates in an effort to acquire data on pre-service teacher perceptions of and attitudes towards Aboriginal perspectives as a field of study and practice. This study found that while some participants reported a great deal of comfort in the study and delivery of Aboriginal perspectives in their respective school experiences, a significant number of participants reported apprehension. The findings of this study suggest that there are a number of variables that may lend to a positive experience for teacher candidates who are responsible for integrating Aboriginal perspectives in their respective practices.

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)0.004
metaresearch head score (Gemma)0.007
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 score0.050
Threshold uncertainty score0.100

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.004
Scholarly communication0.0040.002
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.012
GPT teacher head0.345
Teacher spread0.333 · 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

Citations52
Published2013
Admission routes1
Has abstractyes

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