“The Elders Said if We Stop Fishing We Will Die, We Will No Longer Exist”: Hannah Arendt’s Black Holes, Canadian Corporate Mining Impunity, and Indigenous Narrative Resistance
Bibliographic record
Abstract
Hannah Arendt's Black Holes, Canadian Corporate Mining Impunity, and Indigenous Narrative Resistance Norah Bowman 1Human rights violations in Canada and abroad are endemic to the mining industry.Gordon and Webber's 2016 The Blood of Extraction: Canadian Imperialism in Latin America catalogues Canadian Corporate Mining (CCM) environmental and human rights abuses that, since 2000, have reached an epidemic frequency.Reports by non-profit human rights organizations Mining Watch, Rights Action, San Miguel Ixtahuacán Defense Front, The Justice and Corporate Accountability Project, Unit for the Protection of Human Rights Defenders in Guatemala, Human Rights Watch and Amnesty International document exploitation, human rights violations and disregard of indigenous peoples' rights by CCM.Neoliberal imperialist exploitation scales easily across radically unequal geopolitical regimes; the reports are disturbingly similar in their accounts of exploitation and their calls for justice (Russell, 2016).An unequal balance of economic power between the Global North and Global South, as well as a legacy of power imbalances between colonial states and indigenous peoples underpins this exploitation.Further, legal, financial and moral impunity perpetuates CCM corporate violence; in this essay I examine how impunity in CCM functions and how it can be resisted.CCM impunity works in paradoxical reciprocity with the robust notion of Canada as a uniquely humanitarian nation.As recently as a June 2017, a United Nations Working Group (UNWG) for Business Ethics report to Ottawa, prepared after a UNWG mission to Canada, commends Canada for "demonstrating leadership in promoting human rights, including of women, both within and outside Canada" (UNWG, 2017).The same UNWG report notes that Canadian mining practices abroad and at home fail to "fully address human rights due diligence" (2017).These failures are well documented by human rights organizations who report to the United Nations Working Group 1 Dr. Norah Bowman is a professor cross-appointed to English and Interdiscipliinary Studies at Okanagan College in Kelowna, BC, on unceded Syilx territory.Her work focusses on indigenous and feminist resistance and resilience.
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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 | 0.006 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.051 | 0.061 |
| Scholarly communication | 0.011 | 0.009 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.012 | 0.023 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".