"You Have to Be Involved...to Play a Part in It": Assessing Kainai Attitudes about Voting in Canadian Elections.
Bibliographic record
Abstract
Two days prior to the federal election on June 28, 2004, the Lethbridge Herald ran an article in which the renowned Cree leader and former Member of Parliament Elijah Harper (Churchill electoral district in Manitoba, 1993-97) publicly implored First Nations people in Canada to participate in the forthcoming vote. Citing the recent demographic shift showing a dramatic increase in the number of young First Nations people nationally and their potential ability to influence provincial and federal electoral results, Harper proclaimed that "Native people have a positive role to play in this process." Referring to the endemic lack of voter turnout in recent elections without offering an explanation for these trends, he cautioned First Nations readers that simply following politics from the comfort of one's home was meaningless. Complaining about federal and provincial political matters was not an option, opined Harper, echoing in his concluding comments Michel Foucault's contention that power is contingent and exercised in spatial (political) contexts. Simply put, "You have to be involved [as a voter] ... to playa part in it [Canadian politics)."
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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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".