Theorypracticing Differently: Re-Imagining the Public, Health, and Social Research
Bibliographic record
Abstract
Using a pluralism of critical and deconstructive social theories I explore how we might begin to think differently about the public and health in ways that demand us to also thinkact differently within social inquiries in our transdisciplinary fields. Bringing together multiple concerns for the human, our environments, and the sustainability of our futurities with more-than-human beings, I explore the potentials of thinking through social theories in ways that expand our inquiries toward more just, inclusive, and collaborative anti-disciplinary projects that positively transform social policy and practices. I will conclude by illuminating my own line of inquiry concerning theorypractices—intra-active research entanglements that simultaneously incorporate social theories with methodological design to create positive social transformations in the embodied experiences and material conditions of individuals and groups targeted, silenced, erased, excluded, or neglected within our communities.
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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 | 0.088 | 0.044 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.003 |
| Science and technology studies | 0.015 | 0.244 |
| Scholarly communication | 0.033 | 0.046 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.010 | 0.024 |
| Insufficient payload (model declined to judge) | 0.003 | 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".