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Record W2601239220 · doi:10.1080/02660830.2017.1283758

Colonial encounters in the classroom: Adult educators making sense of Inuit resistance to schooling

2017· article· en· W2601239220 on OpenAlexafffundabout
Scott McLean

Bibliographic record

VenueStudies in the Education of Adults · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsUniversity of Calgary
FundersSocial Sciences and Humanities Research Council of Canada
KeywordsResistance (ecology)ColonialismSociologyAdult educationPedagogyGender studiesPsychologyPolitical science

Abstract

fetched live from OpenAlex

Adult education was an integral component of the colonisation of the Canadian Arctic. Between the 1960s and the 1990s, educational programmes were explicitly developed in order to shape Inuit adults in particular ways: from teaching them how to live in permanent houses, to teaching them how to work as administrators and tradespeople. Inuit did not unanimously embrace such programmes. This article examines how Euro–Canadian adult educators during the 1980s made sense of Inuit resistance to schooling. Educators perceived resistance in terms of ‘problems’ relating to student attendance, punctuality, attrition and work habits. Educators interpreted such problems in terms of individual deficits of motivation and sometimes linked such deficits to cultural or social factors. Educators offered ‘solutions’ ranging from moral exhortation to social marketing campaigns and community-based research. While this article describes how Euro–Canadian adult educators interpreted the resistance of Inuit students, its implications are of value to scholars and practitioners working in a range of contexts where educators and students have different cultural, demographic or socio-economic backgrounds. The article provides a nuanced account of what it is like to be an educator in an environment where many adults do not appear to welcome the education being offered to them.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation 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 score0.137
Threshold uncertainty score0.991

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.031
GPT teacher head0.394
Teacher spread0.363 · 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 teacher head, 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

Citations4
Published2017
Admission routes3
Has abstractyes

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