Bibliographic record
Abstract
This timely and important scholarship advances an empirical understanding of Canada’s contemporary “Indian” problem. Where the Waters Divide is one of the few book monographs that analyze how contemporary neoliberal reforms (in the manner of de-regulation, austerity measures, common sense policies, privatization, etc.) are woven through and shape contemporary racial inequality in Canadian society. Using recent controversies in drinking water contamination and solid waste and sewage pollution, Where the Waters Divide illustrates in concrete ways how cherished notions of liberalism and common sense reform — neoliberalism — also constitute a particular form of racial oppression and white privilege. Where the Waters Divide brings together theories and concepts from four disciplines — sociology, geography, Aboriginal studies, and environmental studies — to build critical insights into the race relational aspects of neoliberal reform. In particular, the book argues that neoliberalism represents a key moment in time for the racial formation in Canada, one that functions not through overt forms of state sanctioned racism, as in the past, but via the morality of the marketplace and the primacy of individual solutions to modern environmental and social problems. Furthermore, Mascarenhas argues, because most Canadians are not aware of this pattern of laissez faire racism, and because racism continues to be associated with intentional and hostile acts, Canadians can dissociate themselves from this form of economic racism, all the while ignoring their investment in white privilege. Where the Waters Divide stands at a provocative crossroads. Disciplinarily, it is where the social construction of water, an emerging theme within Cultural Studies and Environmental Sociology, meets the social construction of expertise — one of the most contentious areas within the social sciences. It is also where the political economy of natural resources, an emerging theme in Development and Globalization Studies, meets the Politics of Race Relations — an often-understudied area within Environmental Studies. Conceptually, the book stands where the racial formation associated with natural resources reform is made and re-made, and where the dominant form of white privilege is contrasted with anti-neoliberal social movements in Canada and across the globe.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.028 | 0.025 |
| Scholarly communication | 0.021 | 0.016 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.006 | 0.008 |
| Insufficient payload (model declined to judge) | 0.029 | 0.003 |
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".