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Record W2281006717

"Our Responsibility to Keep the Land Alive": Voices of Northern Indigenous Researchers

2010· article· en· W2281006717 on OpenAlexaboutno aff
Deborah McGregor, Walter Bayha, Deborah Simmons

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldHealth Professions
TopicIndigenous Studies and Ecology
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousAttendanceSurpriseCorporate governancePublic relationsNarrativePolitical scienceMetisSociologyMedia studiesLibrary scienceManagementLawWorld Wide Web
DOInot available

Abstract

fetched live from OpenAlex

This paper is based on experiences, views, and stories shared by the 22 participants who spoke at the Research the Indigenous Way workshop at the Northern Governance Policy Research Conference in November 2009. The paper does not address all the issues raised, but rather focuses specifically on how the workshop sheds new light on the nature of alternative Indigenous research that would support Indigenous governance. The sharing circle format of the workshop is considered as a model reflecting the research paradigm being talked about. This paradigm requires a critique of past northern “Indigenous” research that perpetuates colonial concepts of governance. Key messages from the groundbreaking work of the Traditional Knowledge Practitioners Group in 2008–2009 are combined with narratives from the 1. This paper would not be possible without the contributions of participants in the Research the Indigenous Way workshop at the Northern Governance and Policy Research Conference (NGPRC), November 5, 2009. The large number of participants that chose to participate in the workshop was a surprise to the coordinators — approximately 30 people were in attendance, and 22 of these shared a story. Verbal permission to record and transcribe the workshop proceedings was obtained at the inception of the workshop. Highlights from the workshop were aired numerous times on the Native Communication Society’s radio station CKLB. The entire transcript was reviewed as the basis for this paper, but only the nine individuals directly quoted in this paper were given an opportunity to review drafts. Each of these has given express consent for use of their quotes, and has provided feedback on the paper as a whole. Special thanks to Alestine Andre, Lia Ruttan, and Celine Mackenzie Vukson who provided detailed input. Thanks also to the two anonymous reviewers whose suggestions helped us to strengthen the paper.

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)0.027
metaresearch head score (Gemma)0.031
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.967
Threshold uncertainty score0.145

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0270.031
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0020.001
Bibliometrics0.0020.002
Science and technology studies0.0420.039
Scholarly communication0.0180.014
Open science0.0040.020
Research integrity0.0090.015
Insufficient payload (model declined to judge)0.0020.001

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 head0.093
GPT teacher head0.448
Teacher spread0.355 · 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.

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

Citations43
Published2010
Admission routes1
Has abstractyes

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