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Record W4389477723 · doi:10.3138/uhr-2022-0032

Anicinabe Aki—Invisible No More: Indigenous Urban History in the Abitibi Region

2023· article· en· W4389477723 on OpenAlexaffvenueabout
Ioana Radu, Nancy Wiscutie-Crépeau

Bibliographic record

VenueUrban History Review · 2023
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsUniversité du Québec en Abitibi-Témiscamingue
Fundersnot available
KeywordsIndigenousFriendshipKinshipColonialismFlourishingPoliticsSovereigntyGender studiesThe ImaginarySociologyPolitical scienceGeographyAnthropologySocial scienceLaw

Abstract

fetched live from OpenAlex

This article explores the Indigenous historiography of the town of Senneterre and the Abitibi region in Quebec. As the centre of ancestral and contemporary social and spatial organization of three Indigenous nations—Anicinabe, Iiyiuu/Iinuu (Cree), and Atikamekw Nehirowisiw—the specificity of Senneterre allows for a more nuanced analysis that centres Indigenous epistemological traditions of kinship, responsibility, and care. We thus focus on the ways in which the Senneterre Native Friendship Centre (and, more broadly, the national and provincial friendship centre movement), through a politics of care, has consistently delinked from settler-colonial tenets to build and embody a vision of making home and weave a sense of belonging for the Indigenous families that have been excluded from the town’s imaginary. The authors show how the Friendship Centre and its members have contributed to the reexamination of analytical and conceptual underpinnings of Indigenous urbanization, from a process of acculturation, cultural and territorial dispossession, and assimilation to that of strengthening contemporary Indigenous identities and the flourishing of a civic society in a place where urban space cannot be disassociated from a complex and overlapping Indigenous sovereign presence.

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)0.001
metaresearch head score (Gemma)0.001
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.059
Threshold uncertainty score0.317

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.007
Science and technology studies0.0060.007
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.049
GPT teacher head0.260
Teacher spread0.211 · 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

Citations1
Published2023
Admission routes3
Has abstractyes

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