Bibliographic record
Abstract
This book explores the relationship between COVID-19 and AIDS. It considers both how the earlier HIV pandemic informed our engagement with COVID-19, as well as the ways in which COVID-19 has changed how we remember and experience AIDS. Individual sections focus on sexual and intimate relationships, inequalities and injustice, the progressive biomedicalisation of the response (in the absence of a vaccine or effective treatment or cure), and professional, practitioner and community perspectives on the pandemics. The authors come from a wide variety of backgrounds – including public health, nursing, law and legal studies, political studies, and the humanities and social sciences. The book contains contributions by established writers such as Dennis Altman, Shalini Bharat, Tim Dean, Deborah Lupton, Shubhada Maitra, Pauline Oosterhoff and Michael Tan, as well as chapters by Chris Ashford and Gareth Longstaff, Bernard Kelly, Dean Murphy and Kiran Pienaar, and Theodore (ted) Kerr. This thought-provoking and timely volume includes case studies from Australia, Austria, Brazil, Canada, Germany, India, Indonesia, the Philippines, the UK, the USA and Vietnam. It has been written for students and scholars from a wide range of disciplinary backgrounds, including sociology, healthcare, public health, social work, anthropology, and gender and sexuality studies. The book will also be of interest to the general reader who wants a better understanding of the social and cultural dimensions of modern-day pandemics and the personal and community responses to which they give rise.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.547 | 0.398 |
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".