MétaCan
Menu
Back to cohort
Record W3194989957 · doi:10.1093/cdj/bsab033

Decolonizing social services through community development: an Anishinaabe experience

2021· article· en· W3194989957 on OpenAlexafffund
Mamaweswen Niigaaniin, Timothy MacNeill, Carola Ramos-Cortez

Bibliographic record

VenueCommunity Development Journal · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicIndigenous Health, Education, and Rights
Canadian institutionsOntario Tech University
FundersIndigenous Services Canada
KeywordsIndigenousDecolonizationParticipatory action researchCommunity developmentCitizen journalismSociologyProcess (computing)Participatory developmentPerspective (graphical)Social changePolitical sciencePublic relationsEconomic growthPolitics

Abstract

fetched live from OpenAlex

Abstract This article is a case study of a community review of an income assistance (IA) program from the perspectives of Anishinaabe First Nations communities that interact with Niigaaniin—an Indigenous-run social assistance program. Using a decolonial methodological approach, the review process revealed that the priority of achieving clients’ wellbeing involves engaging in community wellness and development from an Indigenous community-scale perspective. This participatory review of the program of IA enabled a continued decolonization of social services and community development processes, re-signifying the idea of individual-based social services towards a more Indigenous community-oriented focus. This process suggests that decolonization requires that these separate fields be unified into one participatory, community-centred, and practice.

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)0.011
metaresearch head score (Gemma)0.009
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 score0.986
Threshold uncertainty score0.056

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.009
Meta-epidemiology (narrow)0.0000.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.003
Science and technology studies0.0100.006
Scholarly communication0.0040.003
Open science0.0020.007
Research integrity0.0020.002
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 head0.084
GPT teacher head0.372
Teacher spread0.287 · 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

Citations5
Published2021
Admission routes2
Has abstractyes

Explore more

Same venueCommunity Development JournalSame topicIndigenous Health, Education, and RightsFrench-language works237,207