The Demon of Hope: An Arts-based Infused Meditation on Race, Disability, and the Researcher’s Complicity with Injustice
Bibliographic record
Abstract
My ethical stance demands that my research mutually benefit all research participants and that it should serve to reverse systemic policies of anti-blackness that permeate the educational system in the United States. Through publications and similar academic activities, however, my research advances my own career, but it is doubtful that it significantly advances the trajectories of the students with whom I work. Indeed, it could be argued that this imbalance in benefits advances the very system of white dominance that I claim to contest. In this arts-based, auto-ethnographic study, I document how, through the creation of pastel drawings and digital collage making, I seek to make sense of my compromised role as a white researcher in communities of color. I focus on my recent research with an 18-year-old African-American woman who was diagnosed with ADHD in the 5th grade.
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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 | 0.011 | 0.018 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.016 | 0.056 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.011 |
| Insufficient payload (model declined to judge) | 0.002 | 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 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".