Placing Gender: Exploring Queerness, Rurality, and Non-Normative Gender Experiences
Bibliographic record
Abstract
Placing Gender: Exploring Queerness, Rurality, and Non-Normative Gender Experiences What does it mean to be oneself?To some extent, it involves a personal sense of identity, but humans do not exist in a vacuum; being oneself is often tied up in being one of many, in distinguishing oneself while still being part of a group, and in the places one calls home.Being oneself is a very human concern, but it is also subject to external ideas of what it means to be, how it should be done, where, and with whom, and thus it is worth interrogating these external ideas and the influence they have over one's conception of themselves, their environment, and their community.Drawing on queer, rural queer, and other scholarship, the tangled web of queer gender experiences as they intersect with places and power unravels into interwoven threads of rural, urban, queer, and non-queer normativities and ontologies, all of which shape what it means to be and live out one's gender in a recognizable, happy, willful, queer way, in the city and in the country, to oneself and to others, and inside and beyond normative definitions of being.Before delving into how genders exist in spaces, it seems prudent to explore how those spaces are constructed as rural or urban, with all the baggage those labels entail.There is no perfect urban-rural dichotomy, as "any 'urban/rural' distinction is as much context-specific, phantasmatic, performative, subjective, and... standardizing as it is geographically verifiable," but these are still two ideas worth, if not delineating, then at least characterizing (Herring, qtd. in Thomsen xxvi).Gray Muldoon prefers to use "non-urban," as they view "rural" as a misnomer, "a displaced English motif of the countryside, mismatched to the geography, ecology, and occupations of many non-urban places," but it will be used here, while recognizing the important
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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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.023 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.005 | 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".