Black Feminist Intersectional Methodologies for Life Writing
Bibliographic record
Abstract
This panel is comprised of three black feminist presenters whose research topics and intersectional methodologies are inspired by recognitions of the same gender and genre provocations that drive the work of Canadian auto/biography theorist Marlene Kadar. For the 2017 meeting of the IABA Americas, we present three papers that explore how and where blackness, femaleness, interlocution, Rhetoric Studies, qualitative interviews, gendered cultural studies, and black print culture studies intersect with life writing. Our papers individually and collectively theorize outcomes of life writings by, about, and for black women developed through interdisciplinary and intersectional approaches. Moreover, we analyze ways black women’s life narratives are crafted and/or collected. Our papers investigate diverse processes of generating life writing when auto /biographical subjects are as resistant, elusive, and/or dissident as they are obliging.
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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 | 0.014 | 0.007 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.003 |
| Science and technology studies | 0.014 | 0.022 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.023 | 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".