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 OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.

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.

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)0.006
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Research integrity
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.841
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0060.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.1300.000
Scholarly communication0.0010.002
Open science0.0020.000
Research integrity0.0000.002
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 head0.084
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