Running for elected office: Indigenous candidates, ambition and self-government
Bibliographic record
Abstract
Over the last 40 years, Indigenous communities in Canada have negotiated self-government agreements that allow them to express politically their unique identities, traditions and beliefs within the confines of the federal system. In this paper, we examine the motivations and range of candidates that have run for political office at the regional level in Nunatsiavut, an Inuit self-governing community in northern Labrador created through the Labrador Inuit Land Claims Agreement in 2005. In particular, we examine whether existing political behavior theories are applicable to Indigenous candidates running for office in these kinds of regions. To do so, we qualitatively analyze data from Nunatsiavut elections held between 2006 and 2017, including 11 elite interviews with candidates that ran for the office of Ordinary Member in 2014 and 10 interviews with candidates from other years. Our findings suggest that gender, and to a lesser extent, family dynamics, as well as, public attitudes towards candidates and negative attacks, may be barriers to running for office.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.005 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".