Bibliographic record
Abstract
The science of the human microbiome offers new possibilities for understanding embodiment and health. Microbiome dietary advice seems to celebrate the probiotic ethos of a more-than-human human, of an ecological body open and exposed to the environment, and of microbial life performing essential bodily duties. This science has the potential to explode concepts of individualism and self-control that are fundamental to the ideology of healthism. However, through my analysis of microbiome diet books, I argue that the possibilities of human microbiome science as it is taken up in dietary advice are constrained by the logic of healthism. In so doing, this article demonstrates the pervasiveness of healthist ideology within dietary advice, including discourses that appear liberatory. Instead of freeing the human eater from managerial self-governance, microbiome diet books further entrench practices of control and responsibilization. Dietary advice for the microbiome reveals something about the salience of healthism in U.S. culture—even when confronted with a scientific paradigm that rejects the premise of individualism and control, healthist dietary advice reorients self-governance down to the microscopic scale.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.005 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.002 | 0.013 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.006 | 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".