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Record W4311164775 · doi:10.1163/15718115-bja10096

Dominant Discourse in Indigenous Consultations

2022· article· en· W4311164775 on OpenAlexaffabout
Oxana Pimenova

Bibliographic record

VenueInternational Journal on Minority and Group Rights · 2022
Typearticle
Languageen
FieldArts and Humanities
TopicLanguage, Discourse, Communication Strategies
Canadian institutionsUniversity of Saskatchewan
Fundersnot available
KeywordsArgumentativeArgument (complex analysis)IndigenousContingencyAdversarial systemSet (abstract data type)EpistemologyArgumentation theorySociologyPolitical scienceComputer scienceLawPhilosophyBiologyEcology

Abstract

fetched live from OpenAlex

Abstract In Canada, consulting with Indigenous communities over recourse projects, the Crown sometimes avoids critical engagement with them, holding to the same arguments and counterarguments through regulatory and hearing stages. Such hollow moves, produced under the Crown’s rules, become embedded in the dominant argumentative discourse and pass unnoticed. To detect them, I apply Argument Continuities ( ac s) – a new category of argumentative discourse analysis. ac s are a set of the same arguments and counterarguments repeatedly produced/reproduced by the dominant arguer through an adversarial reasoning process to dismiss opposing arguments. ac s have a specific life cycle – a chain of reasoning dynamics developing in a path-dependent fashion and increasing the cost of adopting a certain argument/counterargument over time. I test ac s in two institutionally diverse cases of Indigenous consultations and argue for the contingency of ac s upon the rules of consultations in reasoning exchanges. Determining the evidence availability and allocating the burdens of proof in consultations, rules make it more or less likely for a dominant arguer to rebut opposing arguments with ac s.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.697
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.022
GPT teacher head0.297
Teacher spread0.275 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations0
Published2022
Admission routes2
Has abstractyes

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