Bibliographic record
Abstract
The realities of political life in Nunavut suggest that levels of political engagement would be lower than that found in southern Canada. The absence of political parties affects both the method of political campaigning and the operation of the legislature while the existence of Inuit birthright organizations provide a parallel system of governance and several more opportunities to vote and to stand for election. Levels of turnout are lower than average for federal elections and lower still for the birthright organizations. For territorial elections, however, turnout levels are much higher. An analysis of predictors of voting demonstrates that age, income and education have a positive impact on turnout. Inuit, and those with positive evaluations of the land claim and Nunavut, are also more likely to vote. In its investigation of political office, the paper also demonstrates that there are elected positions for 1% of the population in Nunavut, compared with .0075% in a typical Canadian community. The paper is the first to examine political behaviour in the North from a quantitative perspective and carefully points out methodological issues affecting the treatment of data. It ends by arguing that southern models of political behaviour should be treated with caution in Nunavut.
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 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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.006 | 0.003 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".