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Record W375326158 · doi:10.5204/ijcis.v5i1.94

Funding and Ethics in Métis Community Based Research

2012· article· en· W375326158 on OpenAlexaffabout
Mike Evans, Chris Anderson, Devin Dietrich, Carrie Bourassa, Tricia Logan, Lawrence D. Berg, Elizabeth Devolder

Bibliographic record

VenueInternational Journal of Critical Indigenous Studies · 2012
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsUniversity of British ColumbiaFirst Nations University of CanadaNational Aboriginal Diabetes AssociationUniversity of Alberta
Fundersnot available
KeywordsHegemonySociologySpace (punctuation)Research ethicsGender studiesEnvironmental ethicsPolitical sciencePoliticsEngineering ethicsLaw

Abstract

fetched live from OpenAlex

Recent ethical guidelines developed by the Canadian Institutes of Health Research along with the Tri-Council Policy Statement: Ethical Conduct for Research Involving Humans stress the importance of Aboriginal community engagement in research. Although these are positive changes meant to ensure respectful and responsive research relationships between communities and researchers, the understanding of 'community' employed by the new guidelines is problematic. In this sense, the guidelines rely on hegemonic understandings of what it is to be an Aboriginal person in Canada, as well as white spatial imaginaries of Aboriginal geographies. In this way, the guidelines codify Aboriginality and its spatiality as that of well-structured, landed, bounded and distinct rural communities. However, the contemporary Métis communities with whom the authors have worked rarely fit into hegemonic imaginaries of Aboriginality and its geographies in Canada. Rather, Métis communities are often institutionally weak, geographically dispersed and sociologically complex. Thus, we argue that the guidelines instantiate a territorialisation of society and space that risks re-marginalising Métis communities.

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)0.316
metaresearch head score (Gemma)0.260
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Research integrity
Consensus categoriesMetaresearch
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.982
Threshold uncertainty score0.843

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.3160.260
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0030.005
Science and technology studies0.0220.042
Scholarly communication0.0210.007
Open science0.0050.013
Research integrity0.0180.016
Insufficient payload (model declined to judge)0.0050.002

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 head0.661
GPT teacher head0.645
Teacher spread0.017 · 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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.

Study designQualitative
DomainMethods
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

Citations25
Published2012
Admission routes2
Has abstractyes

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