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Record W2306940924

Just Do It! Self-Determination for Complex Minorities

2013· dissertation· en· W2306940924 on OpenAlexaboutno aff
Janique Dubois

Bibliographic record

VenueTSpace · 2013
Typedissertation
Languageen
FieldSocial Sciences
TopicEuropean Union Policy and Governance
Canadian institutionsnot available
Fundersnot available
KeywordsPolitical sciencePsychologyData scienceComputer science
DOInot available

Abstract

fetched live from OpenAlex

This thesis explores how Indigenous and linguistic communities achieve self-determination without fixed cultural and territorial boundaries. An examination of the governance practices of Métis, Francophones and First Nations in Saskatchewan reveals that these communities use innovative membership and participation rules in lieu of territorial and cultural criteria to delineate the boundaries within which to exercise political power. These practices have allowed territorially dispersed communities to build institutions, adopt laws and deliver services through province-wide governance structures. In addition to providing an empirical basis to support non-territorial models of self-determination, this study offers a new approach to governance that challenges state-centric theories of minority rights by focusing on the transformative power communities generate through stories and actions.

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)0.005
metaresearch head score (Gemma)0.007
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.010
Threshold uncertainty score0.028

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0100.024
Scholarly communication0.0070.006
Open science0.0010.009
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0040.001

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 head0.070
GPT teacher head0.410
Teacher spread0.340 · 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.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations2
Published2013
Admission routes1
Has abstractyes

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