QUEER (RE)VISIONS OF ARCHIVE, AFFECT, AND PLACE IN CHILD AND YOUTH CARE
Bibliographic record
Abstract
This article presents an autoethnography that interweaves the queering of archive, affect, and place using an object-oriented method. Engaging with a hundred-year-old antique photo album found in a thrift store, this article brings forth queer (re)visions of past, present, and future that (re)imagine queer (be)longing, which expand spheres of ancestral consciousness in 2SLGBTQIAA+ communities. Situated in the United States, this work traces the entanglements in this object-oriented autoethnography through a mapping of queer identity in the Pacific Northwest, capturing temporal reflections that reach from the present back into 1918 and back further still into the early English colonies. In orienting towards the realm of queering child and youth care this work seeks to contribute to a cultivation of discourse of collective (re)visions of past, present, and future that uproots the enshrined settler-colonial, white supremacist, heteropatriarchal, capitalist ethos that continuously crafts the layered erasures of sex, gender, and sexually diverse people in the United States. I endeavour in the threading of autoethnography, both as a white settler and in my being and continually becoming, a genderqueer, trans person struggling and thriving, to critically query the implications of this history within the present and to (re)affirm the possibilities for queer and trans youth in the future.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.032 |
| Scholarly communication | 0.007 | 0.007 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.004 |
| Insufficient payload (model declined to judge) | 0.004 | 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".