Complicating Theory through Practice: Affirming the Right to Die for Suicidal People
Bibliographic record
Abstract
Currently, suicidality is inadequately engaged with in suicide prevention methods. The key focus is on preventing people from dying, rather than validating suicidal ideation as a legitimate experience. As Alexandre Baril (2017; 2018; 2002) argues, in this refusal to validate suicidality, suicidal people are subjected to suicidism – a term Baril coined to describe the oppression suicidal people face which silences them and views their desire to die as illegitimate. Baril (2017) argues for a harm reduction approach to suicide which not only recognizes the validity of suicidality, but also supports suicidal people should they choose to die. In this paper, I seek to highlight Baril’s argument on affirming the choices of suicidal people through an engagement with three of his ideas: epistemic violence, biopower, and the injunction to happiness. While I agree with Baril’s harm reduction approach to suicide, I also contend that his argument becomes more complex when shifting from theory to practice. Therefore, alongside Baril’s work, I highlight the work of Kai Cheng Thom, who recognizes that failing to fight for suicidal people is equally as ableist as failing to listen to them.
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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 | 0.001 | 0.065 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 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".