“That's Just Gonna Make Them Upset”: Youth Authoring Emerging Epistemic Ideals Through Rightful Presence
Bibliographic record
Abstract
ABSTRACT There is a growing body of scholarship in science education that attends to the role of affect as shaping youths' negotiation of and experiences with disciplinary science practices. As part of the special issue Centering Affect and Emotion Toward Justice and Dignity in Science Education, in this paper we examine how power and affect shape epistemic negotiations as youth and adults designed a community survey during a 7th grade biology unit on stress. We used interaction analysis methods to examine how care for the survey takers co‐operatively emerged as an epistemic ideal when creating a community ethnography. The epistemic ideal was shaped by disrupting disciplinary practices, negotiating multidirectional powered adult‐youth relations in the classroom, and youths' positionings in relation with macro‐sociopolitical worlds. How youth characterized care was not neutral but involved youth experiencing politicized empathy towards survey takers coupled with them taking action against survey takers potentially experiencing harm through a tool of Eurocentric science (i.e., the survey). Overall, this work contributes to a critically nuanced understanding of how affect is entangled with and visible through the complex powered dynamics that youth and adults negotiate when engaging in sociopolitical allyship towards more just ways of knowing, examined through the emergence of epistemic ideals within an explicitly justice‐oriented middle school science curriculum.
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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 | 0.009 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.006 | 0.011 |
| Scholarly communication | 0.007 | 0.004 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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".