HYBRID CONSTELLATIONS: EXAMINING SOCIAL MEDIA’S ROLE IN THE MONTREAL LESBIAN SOCIAL SCENE
Bibliographic record
Abstract
This paper examines the role of social media in the definition and organization of lesbian sociocultural landscapes. Building from geographical studies that identify how lesbians’ dispersion across cities counters heteropatriarchal occupations of space, the study is anchored within Montreal/Tiohtià:ke to identify local approaches to visibility and gathering. This angle is combined with digital scholarship that considers how mobile technologies, platforms, and apps give rise to hybrid arrangements that merge physical and digital practices of socialization. These lenses are applied to interviews with representatives from organizations and individuals who use digital technologies to connect lesbians online and across physical space, such as for hosting parties, outdoor activities, and other social gatherings. Preliminary findings show that their use of social media facilitates negotiations of visibility and togetherness while posing definitional challenges. As Montreal’s lesbian networks have become dispersed across the city, multiple modes of communication–from email newsletters to social media–enable meeting across urban space. However, social media pages, events, and accounts necessitate the production of images and text that reflect static definitions of these organizations, the events, and their target audiences. Altogether, we find that social media is a focal tool, among others, to support lesbians’ networked social arrangements but that platforms lack affordances for the fluidity that is integral to ever-fluctuating lesbian/queer identities, locations, and temporalities.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.004 |
| Science and technology studies | 0.014 | 0.014 |
| Scholarly communication | 0.012 | 0.007 |
| Open science | 0.001 | 0.008 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.009 | 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 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".