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Record W3016166364

Institutional Barriers to Community-Based Research: Learning from the Nunavut, Nanivara Project

2018· article· en· W3016166364 on OpenAlexaffvenueabout
Patricia Johnston, Mark Stoller, Frank Tester

Bibliographic record

VenueCritical Social Work · 2018
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsParticipatory action researchIndigenousAction researchPolitical scienceCitizen journalismPublic relationsSociologyPublic administrationEconomic growthPedagogy
DOInot available

Abstract

fetched live from OpenAlex

Participatory Action Research (PAR) is a method of conducting research, understood to be consistent with a decolonizing research agenda. Drawing on experiences from the Nanivara (‘I found it!’) Project, undertaken with youth in Gjoa Haven and Naujaat, Nunavut Territory (2013-2016), institutional barriers to these objectives are explored. While universities and granting agencies have increasingly emphasized the importance of participatory methods and applied research to benefit and help develop the capacity of Indigenous communities, institutional barriers to accomplishing these objectives exist. Research funding bodies and universities have yet to address adequately the significant structural barriers that perpetuate unequal and inequitable relations in the conduct of PAR. This has serious implications for researchers and institutions funding research, where policies and procedures do not easily accommodate the material, social, and geographical realities of Inuit youth.

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 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)0.003
metaresearch head score (Gemma)0.011
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Science and technology studies, Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.531
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0860.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.003
Insufficient payload (model declined to judge)0.0020.002

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 head0.343
GPT teacher head0.510
Teacher spread0.167 · 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; both teacher heads agree on what is shown here.

Study designNot applicable
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

Citations2
Published2018
Admission routes3
Has abstractyes

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