After/Lives: Insights from the COVID-19 Pandemic for Gay Neighborhoods
Bibliographic record
Abstract
Abstract Beginning in 2020, COVID-19 produced shock-shifts that were felt across the globe, not least at the level of the local neighborhood. Some of these shifts have called into question the role of physical places for face-to-face gatherings, including those used by LGBTQ+ people. Such open questions are a key concern for a book on gayborhoods, so this chapter engages in three analytic tasks to provide preliminary reflections on how pandemics problematize places. While acknowledging a range of threats and challenges that the pandemic poses to the future of LGBTQ+ spaces, this chapter focuses on the potential opportunities and unexpected benefits that COVID-19 can create, running counter to more pessimistic predictions that abound in popular discourse. First, the chapter contextualizes how the COVID-19 pandemic is reminiscent of the HIV/AIDS pandemic, allowing the gayborhood to be well-equipped to respond with grassroots activism, particularly in the face of government inaction or apathy. Second, the chapter explores trends that can ensure the future vitality of LGBTQ+ spaces, including (i) the potential of mutual aid networks, (ii) the power of institutional anchors in LGBTQ+ placemaking efforts, (iii) urban changes related to homesteading and population shifts, (iv) innovations in the interior design of physical spaces, and (v) opportunities to enhance social connections through augmented virtual engagements. Far from signaling the death knell of LGBTQ+ spaces, these trends demonstrate the enduring appeal provided by neighborhoods and communities. Third, the cognitive schemas of lockdowns, re-closeting, and digitalscapes are identified as unique expressions of the shifting spatialities of sexuality in post-pandemic urban space. The chapter concludes by arguing that place will still matter for LGBTQ+ people in a post-COVID-19 era, albeit with altered meanings and material expressions. The socio-spatial consequences of the novel coronavirus will be a confluence of positiveandnegative developments, and while some will be reversed as soon as an effective vaccine is found, others will linger indelibly in bodies and the built environment for years to come.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.018 | 0.010 |
| Scholarly communication | 0.011 | 0.008 |
| Open science | 0.002 | 0.008 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".