Tragedy revisited
Bibliographic record
Abstract
“Freedom in a commons brings ruin to all.” So argued ecologist Garrett Hardin in “ The Tragedy of the Commons ” in the 13 December 1968 issue of Science ( 1 ). Hardin questioned society's ability to manage shared resources and avoid an environmentally and socially calamitous free-for-all. In the 50 years since, the essay has influenced discussions ranging from climate change (see page 1217 ) to evolution, from infectious disease to the internet, and has reached far beyond academic literature—but not without criticism. Considerable work, notably by Nobelist Elinor Ostrom ( 2 ), has challenged Hardin, particularly his emphasis on property rights and government regulatory leviathans as solutions. Instead, research has documented contexts, cases, and principles that reflect the ability of groups to collectively govern common resources. To mark this anniversary and celebrate the richness of research and practice around commons and cooperation, Science invited experts to share some contemporary views on such tragedies and how to avert them. — Brad Wible
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 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.002 |
| Science and technology studies | 0.023 | 0.042 |
| Scholarly communication | 0.017 | 0.032 |
| Open science | 0.003 | 0.011 |
| Research integrity | 0.020 | 0.024 |
| Insufficient payload (model declined to judge) | 0.020 | 0.002 |
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".