A Pesquisa em Ciência Política e os Povos Indígenas no Canadá: uma entrevista com Christopher Alcantara
Bibliographic record
Abstract
Christopher Alcantara is a professor of political science at Western University in London, Canada, and has dedicated himself to the study of indigenous peoples and Canadian indigenous politics from this disciplinary field. His book Negotiating the Deal: Comprehensive Land Claims Agreements in Canada, published by the University of Toronto Press in 2013, received several major awards and was a reference for researchers in the field. In this interview, we sought to present this important author of the field of Canadian political science to the Brazilian academic community, reviewing the main arguments of his two most recent books. Alcantara discusses the challenges of doing scientific research that is, at the same time, decolonial and emancipatory, in addition to bringing concrete benefits to the indigenous communities involved. Finally, the researcher gives advice to those who want to start their studies on this topic of research and do not know where to start. With this interview, we aim to strengthen the academic exchange of ideas and research methodologies between Brazil and Canada, instigating the interest of undergraduate and graduate students and students for issues related to the indigenous issue in both countries.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.033 | 0.026 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.004 | 0.007 |
| 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".