The year of the “virtual date”: Reimagining dating app affordances during the COVID-19 pandemic
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The coronavirus disease-19 pandemic introduced a crisis of safety and relevance for dating apps, as their affordances for facilitating in-person encounters posed the risk of viral transmission. This article examines how eight apps primarily catering to heterosexual markets responded to the pandemic through changes to socio-technical arrangements, new user prescriptions, and the curation of corporate data and success stories. By analyzing corporate social media and promotional materials alongside in-app developments, we find that these companies reimagined app affordances to promote “virtual dating,” a set of practices and symbolic meanings that prioritize visual, synchronous digital interaction as the most responsible, reliable, and successful dating approach to the pandemic. Virtual dating centers apps as databases of potential partners while prescribing modes of use aimed toward affective relief, displays of authenticity, and romantic courtship. This reimagining counters moral panics about digitally mediated relationships by resorting to heteronormative dating scripts while overlooking alternative app uses.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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 it