Bibliographic record
Abstract
As a growing global public health concern, an increasing proportion of the UK’s population must live with and manage the chronic disease of food allergies. Through a multi-method approach of autoethnography, cognitive mapping, and interviewing, this research investigates what matters to the bodily experience of people living with food allergies. I work with the concepts of embodiment and affect to delineate a theorisation of the allergic body as recalibratory and argue that the adrenaline auto-injector (AAI)—the lifesaving medication prescribed to individuals with severe food allergies—is integral to the allergic recalibratory body. I demonstrate the multiple, dynamic ways in which those living with food allergies “affectively relate” to the AAI and what contributes to this. An account of the body as recalibratory is advanced to account for the dynamicism of the body’s affective relations. The recalibratory body becomes a valuable tool for understanding the ways that macro-issues of AAI production shortages and the tragic occurrence of allergy fatalities as well as micro-level everyday experiences matter to those living with food allergies. The essay concludes by exploring how the concept of recalibration can expand beyond allergic bodies to understand what the body—any body—can be, do, and mean.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.003 | 0.018 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.002 | 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".