Bibliographic record
Abstract
While studying histories of chattel slavery in Canada, I stumbled upon a ghosted entity that shapes and funds the undercurrents of contemporary carceral power and its expanding reaches through the criminal legal system: the ghost of Canada and western Europe’s enslaving past lives within the body of a global slavery industrial complex. Its haunting structures and enduring tentacles exist within the carceral pathways it paved to enable the emergence of many prison industrial complexes while playing a founding role in the creation and sustenance of white settler nation states. In this chapter I centre slavery’s overlooked and mythologized histories to contextualize chattel slavery’s key role in the onset of many toxic industrial revolutions. I suggest that this created an exploitative economy that institutionalized the use of stolen labour upon stolen lands to create raw materials for Europe to process in factories to sell all over the world. This produced economies that funded the militarized enforcement and expansion of white settler nation states. To understand this larger picture, we are not only required to connect the dots between large historic events we have been taught to see as separate, but also locate chattel slavery’s existence and impacts in places and within economies we have been trained to see as distant or unattached from Europe’s worldwide economies of chattel slavery.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.023 | 0.022 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.010 | 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".