Bibliographic record
Abstract
This commentary builds on my presentation in the panel “Revisioning Feminist Engagements with Madness” at the 2023 Women’s, Gender, and Social Justice annual conference. In doing so, this piece grapples with several debates surrounding the stigmatized psychiatric label of “borderline personality disorder (BPD).” While feminists have long called for the diagnosis to be removed or replaced, Mad-affirmative scholars are reconceptualizing borderline as a cluster of insightful experiences and psychocentric activists are trying to destigmatize and raise awareness about “BPD.” The latter two efforts are very different from each other, yet both seem to be located in white, globally elite spaces. This piece suggests that we can learn from other reclamation movements that, co-opted by the colonial state and neoliberal market, have mainly benefited elites, and thus cautions against any attempt to universally reclaim, reject, or reconceptualize borderline. That is, rather than unpacking what borderline really is or should mean, this piece asks what borderline does, for whom, in which contexts, and towards what ends. Drawing from Gilles Deleuze’s ethological method and Jasbir Puar’s work on debility and capacity, this article acknowledges the socio-political patterns of borderline, as well as the broader systems we might be serving in our seemingly progressive discourses.
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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 | 0.041 | 0.040 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.030 | 0.073 |
| Scholarly communication | 0.017 | 0.016 |
| Open science | 0.004 | 0.013 |
| Research integrity | 0.018 | 0.034 |
| Insufficient payload (model declined to judge) | 0.006 | 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".