Proceedings of the Workshop on Future Directions for Common Property Theory and Research, Rutgers University New Brunswick, NJ
Bibliographic record
Abstract
"The Common Property Workshop at Rutgers was co-hosted by the Ecopolicy Center for Agricultural, Environmental, and Resource Issues and the International Association for the Study of Common Property, IASCP, which held its Executive Board meeting the next day (March 1st). Bonnie McCay, Associate Director of the Ecopolicy Center and Professor in the Department of Human Ecology at Rutgers University, organized and chaired the workshop. In her introductory remarks she said, 'we couldn't pass up this opportunity to bring together people who are doing the most innovative thinking about the problems of dealing with common resources, as well as the problems of property rights and property rights as they relate to and use of management of natural resources.' She introduced members of the Executive Board of IASCP and other participants. Then Bob Tucker, director of the Ecopolicy welcomed the group on behalf of Rutgers University. He explained the Ecopolicy Center, which looks at resource issues from an environmental point of view, ecological point of view and also an economic point of view. We're looking at environmental issues at agricultural issues, issues of land use, and so the idea for looking and studying common property is very appropriate for the center. We're also particularly proud to have Bonnie as the President-elect of the International Association of the Study of Common Property. So I think it is particularly appropriate that you are all here this afternoon - welcome."
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 | 0.011 | 0.016 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.006 |
| Scholarly communication | 0.012 | 0.013 |
| Open science | 0.004 | 0.004 |
| Research integrity | 0.005 | 0.007 |
| Insufficient payload (model declined to judge) | 0.083 | 0.011 |
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".