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Record W2966800964 · doi:10.26203/zm8m-wa24

Reconciliation, resilience and resistance in Inuit teacher's professional development and practices

2019· article· en· W2966800964 on OpenAlexafffundabout
Kathy Snow, Shelly Tulloch, Heather Ochalski, Melanie O’Gorman

Bibliographic record

VenueWinnSpace (University of Winnipeg) · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsInuit Tapiriit KanatamiUniversity of WinnipegCape Breton University
FundersSocial Sciences and Humanities Research Council of CanadaArcticNet
KeywordsChristian ministryResilience (materials science)Resistance (ecology)Professional developmentPsychological resilienceLibrary sciencePolitical scienceSociologyPedagogyPsychologyBiologyEcologyComputer scienceSocial psychology

Abstract

fetched live from OpenAlex

Acknowledgements We are extremely grateful to the Inuit teachers and long-term northern educators from all Inuit regions who were able to participate, and for the community of Nain, Nunatsiavut for hosting the Forum. We want to highlight the support of ArcticNet, the Nunatsiavut Ministry of Education and Economic development, ITK and the SSHRC for their financial and in-kind support in the form of time and resources. We also thank Shanti Subedar (student at the University of Winnipeg) who transcribed Forum recordings.

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)0.007
metaresearch head score (Gemma)0.011
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 score0.550
Threshold uncertainty score0.896

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.011
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.001
Science and technology studies0.0390.019
Scholarly communication0.0090.004
Open science0.0030.013
Research integrity0.0020.004
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 head0.014
GPT teacher head0.273
Teacher spread0.259 · 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".

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Citations1
Published2019
Admission routes3
Has abstractyes

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