Securitization of Mental Health: An Analysis of Ellen Richardson and the ‘Indiscriminate Disclosure’ of Mental Health Records
Bibliographic record
Abstract
This thesis applies theoretical contributions of Michel Foucault and Giorgio Agamben to provide a framework for understanding the disclosure of mental health information to U.S. authorities for the purpose of traveller preclearance screening. Exploring the implications of biopolitics and governmentality, I investigate the case of Ellen Richardson, a Toronto woman who was denied entry to the U.S. for having a failed suicide attempt on her special interest to police record. Beginning with Foucault's (1995) work in Discipline and Punish: The Birth of the Prison, this thesis explores the depths of governmental control and regulation as they pertain to the collection and disclosure of sensitive mental health information. This thesis examines how mental health has become a 'risk' metric to determine a person's inadmissibility and points to the growing reliance on police intelligence on attempted suicide to infer a history of mental illness as the source of contention.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".