Bibliographic record
Abstract
In many ways, this is a very special issue.To those who embody historically marginalized identities and/or care about social justice, it has been hard to find joy these days.Yet, joy, or at least talk about joy, seems to be everywhere.From activist affirmations to neoliberal cooptations.In podcasts, mapping projects, and even in the latest US presidential election.Defined by Kristie Soares as "both a scholarly field and an activist movement dedicated to examining how joy functions as a form of political resistance among minoritized communities," critical joy studies is still an emerging field.Along with the American Historical Association panel mentioned by Soares in their field-defining piece here, this issue is an attempt to bring together people who are thinking critically about joy in/from different disciplines and fields and provides an exciting dialogue between academics, artists, and activists, as well as folks who defy these boundaries.This issue is also special on a personal level because it will be my last as a JFS coeditor, and I could not think of a better way to conclude this trajectory.I met Miguel Valerio when I served as a guest editor for JFS issue #3 and have been a fan of his work since.At the time, we were both writing books that, in very different ways, dealt with joy and celebration as forms of resistance.While his work has certainly inspired my approach to joy and celebration studies, Miguel also inspires me because he possesses a quality rare in academia.He not only studies and beautifully writes about solidarity, justice, and resistance, but he also embodies that in praxis.It has been an honor, a joy, and a pleasure to conceptualize and see this through with you, meu amigo!
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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 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.004 | 0.006 |
| Insufficient payload (model declined to judge) | 0.232 | 0.123 |
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".