The Fragility of a Mighty Process: Capital and Cattle Mutually Assist their Reproduction
Bibliographic record
Abstract
Lylehaven Lila Z is a Canadian Holstein also known as the "million-dollar cow." 1 Cows have a gestation period of nine months and have one calf a year.However, Lila has sixty-seven offspring registered in Canada and fifty more in the rest of the world, but she is only nine years old.Her secret?A multispecies bio-capitalist technology called "embryo transfer" and the value it places on the productivity of her ovaries.Responding to hormonal stimulus, Lila's ovaries generate many eggs, which, with unusual frequency, pair up with the inseminating sperm, resulting in an unusually high number of embryos.Extracted from Lila, these are transferred to other cows' uteri for their gestation; they will birth calves bequeathed with Lila's ovulatory quality (and superb milk productivity).Enabling Lila's embryo makingand her price tag-is artificial insemination or AI, also used in cutting-edge technologies such as CRISPR to produce genet ically edited cows and bulls.At its most quotidian level and simplest definition, AI is a human-mediated agricultural practice that uses genet ically certified bull semen (extracted and turned into a commodity) to impregnate cows, reproduce cattle, and eventually improve the herd.Artificial insemination acquired recognition as an efficient agricultural technology throughout the 1930s.It peaked by the end of World War II, becoming a worldwide boom starting in the 1950s. 2 Confident enthusiasm met the emerging practice: "Some remarkable effects can be produced on animals now that human beings are learning to take charge of the directing glands" (Russell 1966, 336, cited in Clarke 2007, 319).Currently,
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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 | 0.004 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.009 | 0.030 |
| Scholarly communication | 0.013 | 0.010 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.021 | 0.003 |
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".