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Record W4411170338 · doi:10.17161/gjcpp.v11i3.20663

Social Representations of Indigenous People within a sample of non-Indigenous Young in Quebec, Canada

2020· article· en· W4411170338 on OpenAlexaffabout
Thomas Saïas, Mathilde Perray, Karen Devaud, Johanna Nouchi

Bibliographic record

VenueGlobal Journal of Community Psychology Practice · 2020
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversité du Québec à Montréal
Fundersnot available
KeywordsIndigenousSociologySample (material)GeographyGender studiesAnthropologyEcologyBiologyPhysics

Abstract

fetched live from OpenAlex

Relations between Indigenous and non-Indigenous people in Quebec have been characterized by cultural and political domination by European-Canadian populations. Recently, a pro-reconciliation political movement has emerged and is trying to ease these relations. The purpose of this study was to evaluate the extent to which the pro-reconciliation discourse has succeeded in being integrated into the social representations of the youngest Quebeckers. Using a qualitative methodology, we have highlighted that a paternalistic discourse remains, as well as elements of representation that identify indigenous people as diseased, helpless and freeloaders. The discussion focuses on the dangers of a reconciliation approach that would only emphasize the place of Indigenous people without taking into account the obstacles generated by the implicit prejudice of social representations.

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)0.002
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.031
Threshold uncertainty score0.228

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0120.004
Scholarly communication0.0030.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.062
GPT teacher head0.451
Teacher spread0.389 · 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 designObservational
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
Published2020
Admission routes2
Has abstractyes

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