Keeping the Conversation Going: Rendering Each Other Capable While Creating Zines
Bibliographic record
Abstract
In response to Lee de Bie and Kate Brown’s webinar on neuroatypicality in academia, Lieve Carette and Lee de Bie delve into the concept of “relational access” and its transformative influence on neurodivergent relationships, overcoming obstacles and expanding possibilities of support. Drawing inspiration from the creative initiatives of Mad and neurodivergent students and staff reshaping the academy, the authors share insights from their 6-year friendship, exploring the challenges of navigating university through neuroatypicality. Their interconnected reflections underscore the importance of facilitating the creation of the zine “Outliers” in shaping their dialogues. Within the context of Qualitative Inquiry, this article indirectly explores zines as an academic methodology, emphasizing the integral role of the intimate relationship in zine project development and personal and professional growth. The paper concentrates on the zine’s impact within their relationship, accentuating its modest contribution to the project’s inception compared with its substantial significance in their lives and personal growth.
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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 | 0.015 | 0.023 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.015 | 0.025 |
| Scholarly communication | 0.012 | 0.019 |
| Open science | 0.002 | 0.027 |
| Research integrity | 0.002 | 0.007 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".