Summer reading 2023 <b>In a Flight of Starlings: The Wonders of Complex Systems</b> , <i>Giorgio Parisi</i> , Penguin Press, 2023, 144 pp. <b>I Feel Love: MDMA and the Quest for Connection in a Fractured World</b> , <i>Rachel Nuwer</i> , Bloomsbury, 2023, 384 pp. <b>Many Things Under a Rock: The Mysteries of Octopuses</b> , <i>David Scheel</i> , Norton, 2023, 320 pp. <b>The Hidden History of Code-Breaking: The Secret World of Cyphers, Uncrackable Codes, and Elusive Encryptions</b> , <i>Sinclair McKay</i> , Pegasus, 2023, 400 pp. <b>Thinking with Your Hands: The Surprising Science Behind How Gestures Shape Our Thoughts</b> , <i>Susan Goldin-Meadow</i> , Basic Books, 2023, 272 pp. <b>The Madwomen of Paris: A Novel</b> , <i>Jennifer Cody Epstein</i> , Ballantine Books, 2023, 336 pp. <b>Life on Other Planets: A Memoir of Finding My Place in the Universe</b> , <i>Aomawa Shields</i> , Viking, 2023, 352 pp. <b>The Ghost Forest: Racists, Radicals, and Real Estate in the California Redwoods</b> , <i>Greg King</i> , PublicAffairs, 2023, 480 pp. <b>The Quickening: Creation and Community at the Ends of the Earth</b> , <i>Elizabeth Rush</i> , Milkweed Editions, 2023, 424 pp.
Bibliographic record
Abstract
No abstract. This is not a gap in this database; OpenAlex has none either. 23.3% of the frame is in this state, and the screen finds HALF as much metaresearch here, so the absence is a measured bias rather than a missing field.
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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.155 | 0.078 |
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".