The Friction of Digital Queer Worldbuilding; \nQueer women from Montreal and the intersections between sexuality and collective identity.
Bibliographic record
Abstract
The online world and the ‘real’ world. In the last thirty years, the gap between the two has only blurred. Alongside this evolution is a generation of young women who have had their concept of sexual identity shaped by their interactions online. By applying ethnographic fieldwork in Montreal, this thesis examines the friction that exists between these young queer women, their concepts of self, and collective identity building both in Montreal and online. The research accomplishes this through observation of group discussions, as well as one on one ethnographic interviews. Montrealers' feelings about their sexuality is often complicated by the tension between personal feelings and group doctrine. Due to heteronormativity, these young queer women have been left without a strong cultural foundation to build their sexual identity onto, seeking out a sense of belonging and community. That sense of belonging is often unavailable or lacking offline for several reasons. This leads young queer women to seek online community. Yet the nuances of human sexuality and gender often leave women worried that they do not fit a certain mold of queerness within these online communities. Despite this, young queer women report these spaces as vital to their understanding of themselves. Through an analysis of queer worldbuilding and imagined communities, this thesis challenge more traditional modes of understanding community by analyzing how online space interacts with participants' sense of community.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.019 | 0.009 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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".