Bibliographic record
Abstract
Geoffrey Lloyd has just summarized, in a few pages, his superb Cognitive variations: Reflections on the unity and diversity of the human mind (Lloyd 2007). It serves its purposes well, of trying to reconcile our evident psychic diversity with our shared humanity (27). I have nothing to add to that project here. When I reviewed the book in 2007, I called it the best overall state of play on the current game of nature v. nurture.1 (That is the v. for versus, chosen by the British editors.) I recommend the book not only to those sympathetic to his essay-abstract here, but also to those who disagree, for its arguments, at greater length, are often more compelling than they appear when summarized. Lorraine Daston cavils at the v for versus, and also at the more usual nature versus culture. She brings the metaphor of culture to life once again, as in cultivation and horticulture. I wish her well. I confess that in 2007, I had already given up on the word culture as an all too dead metaphor, in part because I was convinced by its sorry tale as told by the anthropologist Adam Kuper (1999). Nurture, on the other hand, has been so long untilled that it can spring to life with only a little light watering. As I wrote in my review of Lloyd,
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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.007 | 0.008 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 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".