Bibliographic record
Abstract
Across North and South America, Indigenous people play a dual political role, building self-governing structures in their own nations and participating in the elections of settler states. Doing Democracy Differently asks how states are responding to demands for Indigenous representation and autonomy and in what ways the ongoing project of decolonization may unsettle the practice of democracy. Based on the structured, focused comparison of four success stories across Northern Canada, Bolivia, and Ecuador, this book provides real-world examples of how Indigenous autonomy and self-determination may be successfully advanced using existing democratic mechanisms. Drawing on thorough original research to identify factors that create distinctive patterns within Indigenous-state relations, it argues that the capacity for democratic innovation lies within the realm of civil society while the possibility for uptake of such innovation is found within the state and its willingness to work with Indigenous and popular actors. Operating at the intersection of Indigenous and Comparative Politics, Doing Democracy Differently takes seriously the role of institutions and the land on which they are built in the creation of democratic transformations in the Americas. This book advances Indigenous rights to autonomy and self-government and speaks to some of the thorniest issues in democratic governance.
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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 | 0.002 |
| 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 | 0.012 |
| Scholarly communication | 0.009 | 0.008 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.006 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".