Reflections on Presumed Incompetent: The Intersections of Race and Class for Women in Academia Symposium - The Plenary Panel
Bibliographic record
Abstract
Presumed Incompetent was produced thanks to the vision and commitment of its editors: Dr. Gabriella Gutiérrez y Muhs, Dr. Yolanda Flores Niemann, Carmen G. González, and Angela P. Harris. This symposium came to fruition because the Berkeley Journal of Gender, Law & Justice invited the two law professor editors, Professor Harris and Professor González, to convene a distinguished group of scholars from Canada and the United States to expand and deepen the conversation initiated by the book. The very successful day-long symposium and the publication of the resulting articles were made possible by the resources, time, and dedication provided by the University of California Berkeley School of Law, the Berkeley Journal of Gender, Law & Justice, the Seattle Journal for Social Justice, the Thelton E. Henderson Center for Social Justice, and the generous support of the law firm of Munger, Tolles & Olson. Finally, the audience, a mix of academics and students, supported the symposium and traveled from all over the United States to attend and be a part of a historical event where we acknowledged the pain and victories of colleagues, and recognized that there is still much work to be done. The plenary panel proceeded as follows. First, the panelists gave brief opening remarks about their chapters, followed by a question and answer portion, and ended with my closing remarks. Members of the audience submitted questions once the plenary panel discussion began. While this Article is not a verbatim transcript of the plenary panel, all the questions are the same ones posed during the panel. The remarks and answers included here follow a semi-transcript format that allowed the moderator and panelists an opportunity to elaborate further on some of the comments and responses.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.031 | 0.010 |
| Scholarly communication | 0.019 | 0.011 |
| Open science | 0.003 | 0.014 |
| Research integrity | 0.015 | 0.024 |
| Insufficient payload (model declined to judge) | 0.017 | 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".