Sensoria Special Edition on Sexual Orientation and Gender: Editorial
Bibliographic record
Abstract
This Special Edition of Sensoria: A Journal of Mind, Brain, and Culture presents a series of integrated papers that address the intersection of gender and sexual orientation. We have had the privilege to work with a high quality panel of contributors to this special edition, to whom we are grateful for their support and time. Finally, the high quality of the articles published in this special edition of Sensoria would not have been possible without our expert panel of international reviewers. Their generous contributions have helped improve the quality of the work that we are able to present to you. We would like to acknowledge the following reviewers: Fiona Barlow (University of Queensland, AUS), Thekla Morgenroth (University of Exeter, UK), Rose Ferguson (Australian Catholic University, AUS), Yasin Koç (University of Sussex, UK), Jodie Chapman (Monash University, AUS), Leah Kaufmann (Australian Catholic University, AUS), Todd Morrison (University of Saskatchewan, CAN), Shaun Pichler (Royal Melbourne Institute of Technology, AUS), and Christopher Hunt (University of Trieste, ITA). We also extend our thanks to those who chose to remain anonymous in reviewing articles included in this special edition.
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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 | 0.005 | 0.034 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.002 |
| Bibliometrics | 0.006 | 0.003 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.003 | 0.002 |
| Research integrity | 0.006 | 0.009 |
| Insufficient payload (model declined to judge) | 0.019 | 0.008 |
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".