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Record W3205614656 · doi:10.3390/educsci11100627

Knowledge versus Education in the Margins: An Indigenous and Feminist Critique of Education

2021· article· en· W3205614656 on OpenAlexaff
Anna Lydia Svalastog, Shawn Wilson, Ketil Lenert Hansen

Bibliographic record

VenueEducation Sciences · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicQualitative Research Methods and Ethics
Canadian institutionsOkanagan University CollegeUniversity of British Columbia, Okanagan CampusUniversity of British Columbia
Fundersnot available
KeywordsNarrativeTraditional knowledgeSociologyIndigenousGuard (computer science)Pedagogy

Abstract

fetched live from OpenAlex

This article highlights the perceptions and expectations of knowledge that many people, including educators and policy makers, take for granted. Our focus of understanding is Indigenous studies and gender studies. Our aim is to show how modern education undermines these fields of studies. We use an autoethnographic method, reflecting more than 75 years as pupils/students and more than 90 years as educators. We have carefully chosen narratives of exposure to knowledge outside the educational system, as well as narratives of limitations posed upon us by the educational system. This narrative approach makes it possible for us to investigate and discuss our grief about areas of knowledge that society cries for, but the educational system continuously finds ways to resist. Our conclusion is that crucial knowledge is located outside the educational system, where individuals, groups, and communities cherish, protect, and guard knowledge that the educational system marginalises or excludes. As this knowledge is fundamental for life, our message is that the educational system needs to re-evaluate its strategies to stay relevant.

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)0.007
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 score0.448
Threshold uncertainty score0.975

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.296
GPT teacher head0.649
Teacher spread0.353 · 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

Citations5
Published2021
Admission routes1
Has abstractyes

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