Non-binary superpowers! a collaborative conversation between non-binary youth in Adelaide, South Australia, and non-binary youth in Calgary, Alberta
Bibliographic record
Abstract
A common experience of folks who identify outside of binary gender is that of erasure, an experience of not being seen, fighting daily to 'prove' that our identities and experiences are 'real' and 'valid'. In April and May of 2019, two small groups of Trans and Non-Binary (enby) young people and some of their loved ones came together on opposite sides of the world. Tiffany Sostar (they/them) and Rosie Maeder (she/ her) hosted narrative conversations in Adelaide, Australia, and Calgary, Canada, and linked them through a collective document. This was the beginning of an ongoing trans-continental conversation exploring the skills, knowledges and experiences of Non-Binary young people and of the ways they are or hope to be seen and supported by loved ones. Tiffany and Rosie hoped to draw out rich, multi-storied accounts of Non-Binary experiences and to make visible the skills, knowledges and complicated superpowers required to resist rigid constructs of gender. They seek to further subvert Non-Binary invisibility by sharing these stories with other enby folks and anyone else who wants to learn more about Non-Binary experiences or identities ‒ including and especially Narrative Practitioners who work with Trans and Non-Binary young people.
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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 | 0.005 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.036 | 0.015 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.011 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.004 | 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".