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Record W2994928319 · doi:10.37119/ojs2019.v25i2.443

Place-Based Readings Toward Disrupting Colonized Literacies: A Métissage

2019· article· en· W2994928319 on OpenAlexaffvenueabout
Adrian M. Downey, Rachael Bell, Katelyn Copage, Pam Whitty

Bibliographic record

Venuein education · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous and Place-Based Education
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsColonialismIndigenousReading (process)PremiseLiteracySociologyCurriculumAestheticsPedagogyHistoryPolitical scienceLinguisticsArtLawEcologyArchaeologyPhilosophy

Abstract

fetched live from OpenAlex

Working from the premise that learning to live well in our places is quickly becoming a necessity of human survival, in this article we weave together divergent experiences of our shared place, the Wabanaki Confederacy or Eastern Canada, and literatures and literacies of that place. This article is methodologically framed using the concept of “métissage” as it has been taken up in Canadian curriculum studies as a form of intertextual life writing. Through our métissage, we are ultimately concerned with theorizing the idea of reading place—making sense of the ways in which settler colonialism has historically made, and continues to make, itself felt on Land. The idea of reading place, however, also demands that we actively engage in disrupting the normativity of settler colonial presence on Land—particularly as manifest through literature and literacy. Toward speaking back to the normativity of this settler colonial presence, the authors draw on divergent pedagogical and literary practices toward ensuring indigenous futurities. Keywords: settler colonialism; literacies of the land; literacy

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)0.006
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 score0.100
Threshold uncertainty score0.199

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.001
Science and technology studies0.0150.049
Scholarly communication0.0100.005
Open science0.0010.011
Research integrity0.0010.004
Insufficient payload (model declined to judge)0.0020.000

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 head0.015
GPT teacher head0.327
Teacher spread0.313 · 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

Citations3
Published2019
Admission routes3
Has abstractyes

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