What Does Borderline Do? Thinking with Debility and Capacity
Bibliographic record
Abstract
Abstract This essay grapples with several debates surrounding “borderline personality disorder (BPD),” a highly stigmatized and gendered psychiatric label disproportionately given to cisgender women and used to invalidate their experiences. There is a growing effort to destigmatize “BPD”—particularly on social media—and advocate for better treatment. However, these movements can overlook long-standing feminist critiques of the diagnosis itself, as well as Mad feminist interventions that affirm borderline epistemologies while critiquing psychiatry. This essay interrogates how and why both mainstream and Mad approaches to destigmatizing “BPD” seem to be located in White, globally elite spaces. We argue that any universalizing attempt to reconceptualize “BPD” risks benefiting elite borderlines and the neoliberal state while continuing to criminalize, pathologize, and neglect structurally precaritized people who are labeled with “BPD.” Rather than unpacking what “BPD” really is or should mean, we explore what “BPD” does, for whom, in which contexts, and toward what ends.
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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 | 0.008 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.009 | 0.083 |
| Scholarly communication | 0.010 | 0.015 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 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".