Bibliographic record
Abstract
Anyone who has ever lived with roommates understands the Hobbesian state of nature implicitly. People sharing accommodations quickly discover that buying groceries, doing the dishes, sweeping the floor, and a thousand other household tasks, are all prisoner's dilemmas waiting to happen. For instance, if food is purchased communally, it gives everyone an incentive to overconsume (because the majority of the cost of anything anyone eats is borne by the others). Individuals also have an incentive to buy expensive items that the others are unlikely to want. As a result, everyone's food bill will be higher than it would be if everyone did their own shopping. Things are not much better when it comes to other aspects of household organization. Cleaning is a common sticking point. Once there are a certain number of people living in a house, cleanliness becomes a quasi-public good. If everyone ‘pitched in’ to clean up, then everyone would be happier. But there is a free-rider incentive—before cleaning, it's best to wait around a bit to see if someone else will do it. As a result, the dishes will stack up in the sink, the carpet will get grungy, and so on.
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 | 0.008 | 0.014 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.007 |
| Scholarly communication | 0.006 | 0.010 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.011 | 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".