'Don't Read the Comments!' Reflections on Writing and Publishing Feminist Socio-Legal Research as a Young Scholar
Bibliographic record
Abstract
This article responds to reviews written by Eve Darian-Smith and Mehera San Roque and published in Feminists@Law. Darian-Smith and San Roque's reviews focus on the contributions made by my 2011 book, Murder, Medicine and Motherhood. In this response, I have taken the opportunity to reflect a little on the experience of writing Murder, Medicine and Motherhood, and on its reception. In the first section, I trace the choices and unanticipated challenges that structured my research for Murder, Medicine and Motherhood. Both Darian-Smith and San Roque have commented on this methodology, and I have noticed that after publication, the scope and content of the finished product of a research project can seem inevitable. I try to unpack that appearance, because I think that there can be value in trying to remember why certain choices were made at certain times, and in pondering the accidents that prompt turns within one’s work. The following section considers the transition that takes place when a published work enters the field and in fact changes the topic of research in certain ways. Given the media attention that my conclusions have attracted and the possibility that Kathleen Folbigg’s case may now be reviewed, Murder, Medicine and Motherhood has to some extent had this effect. In the course of my work becoming a more public product, my conclusions and my sense of myself as an academic have also been challenged at times. The rewards and perils of media engagement form a topic that is occasionally discussed in the literature, but rarely with regard to explicitly feminist work. Given that academics are increasingly exhorted by our employers and research funding agencies to demonstrate the public relevance of our work, and to engage with mass media, it seems important to consider the possibilities and the pitfalls of such engagement from a feminist perspective.
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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 | 0.067 | 0.135 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.003 |
| Science and technology studies | 0.041 | 0.045 |
| Scholarly communication | 0.036 | 0.023 |
| Open science | 0.004 | 0.015 |
| Research integrity | 0.018 | 0.034 |
| Insufficient payload (model declined to judge) | 0.009 | 0.004 |
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".