Mining liquid gold: The lively, contested terrain of human milk valuations
Bibliographic record
Abstract
As global health organizations and national governments tout "breast is best," the value of human milk is being calculated - and profited from - in increasingly diverse forms. In this paper I chart three of the major ways in which human milk is being economically valued: calculating breastfeeding as a contribution to a country's GDP; buying and selling human milk to hospitals for profit; and manufacturing key components of human milk and the infant gut. In exploring these bioeconomies, I draw together two approaches to biocapital not often put into conversation with one another: a focus on the micrological generative capacities of biological material, and attention to the macrological biopolitical governance of populations. I argue that juxtaposing these bioeconomies demonstrates key features of human milk biocapital: the multi-scalar workings of reproductive biopolitical valuation and governance; the human and more-than-human ecologies (and labours) on which biocapital depends; and the feminist geographical contestations that shape, and sometimes undermine, these valuations.
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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 | 0.005 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.044 |
| Scholarly communication | 0.008 | 0.005 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.001 |
| 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".