Bibliographic record
Abstract
The aim of this paper is to unsettle dominant discourses about the state and forensic social work though “dehistoricization” through two historical case studies from Canada: the eugenics movement and the Indian Act. This critical and structural analysis will demonstrate how the state historically and contemporarily disproportionately disadvantages disabled and Indigenous peoples independently and intersectionally through social control tactics. Using a conceptual framework from Foucault’s History of the Present approach, I problematize how historical practices manifest in present-day technologies of the state. I also utilized Blackstock’s Touchstones of Hope, a model for reconciliation in children’s services through four phases: Truth Telling, Acknowledging, Restoring, and Relating. After situating myself in the work, I will then articulate the key concepts including forensic social work, the state, intersectionality, and settler colonialism followed by the dominant historical discourses in forensic social work. Next, I dehistoricize the eugenics movement and the Indian Act as case studies to demonstrate how the state used and uses social control tactics of surveillance, categorization, segregation, and containment of disabled and Indigenous peoples. Contemporary forensic social work practices with disabled and Indigenous peoples will demonstrate that the historical practices continue in the present. I conclude with a call for reconciliation and transformative change.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.001 | 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 | 0.016 | 0.018 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| 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".