Violence as civility: race, mining and Canadian neocolonizers in African states
Bibliographic record
Abstract
Occupying a dominant position in the global mining industry is one of Canada's key strategies for establishing itself as a successful nation in the twenty-first century global order. This has entailed a rapid expansion of Canadian mining industry presence in African states, such that Canada is now the leading non-African country investing in African mineral exploration. Positing such presence as neocolonialist in nature, this thesis asks how it is in cultural terms that Canada, a country usually portrayed as a model of national and international civility, is able to engage in inherently violent neocolonialist practices in African countries in the twenty-first century. Data is generated primarily from interviews with Canadian mining industry professionals, and supplemented with examination of various Canadian federal government texts, multilateral agency documents and mining industry documents. The data is read in relation to the fact of African resistance to foreign domination of mining. Drawing on anti-colonial, postcolonial, post-structural and critical race theories of white masculinity, nation formation and racial discourse, my analysis of the data shows the making of a particular kind of Canadian national cultural imaginary, 'muscular white civility'---and a particular type of white male capitalist subject---required to normalize contemporary processes of North-South resource appropriation. By authorizing the appropriation of African mineral wealth in the name of Canadians' 'muscular white civility' (we have capital, technology, organization and humane values), Canadians' privileged access and property rights are maintained and normalized in contemporary African mining. A key finding of this research is the inherently white supremacist nature of the Canadian twenty-first century internationalist imaginary and the consequent reproduction of North-South economic disparities structured along racial lines.
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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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.006 |
| Science and technology studies | 0.025 | 0.011 |
| Scholarly communication | 0.005 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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".