Common Challenges: Policy, Theory and Voice
Bibliographic record
Abstract
"Berge and Prakash reflect on the role of IASC in light of the inclusion of commons research in other fora and increasing diversity in the IASC membership. Both of these trends are to be rejoiced yet force us to ponder the Associations future directions. Two decades of IASC have seen the commons transformed from a tragedy into an opportunity, from a rogue line of research into accepted practice. Given this success, one IASCs conferences as part of these projects. This creates interest, diversity and breadth of participation at conferences, but it also means there is a substantial 'floating' membership and turnover in participation from one conference to the next option is to simply disband IASC and allow its members to gravitate to other fora. Yet while the idea of the commons has gained currency elsewhere, the Association lies at the intersection of research and practice. To build on this position over the next two decades, IASC must understand how commons research is used, link practice back into theory, and strengthen the voices of Southern members."
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 | 0.054 | 0.084 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.002 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.036 | 0.107 |
| Scholarly communication | 0.041 | 0.057 |
| Open science | 0.009 | 0.038 |
| Research integrity | 0.044 | 0.026 |
| Insufficient payload (model declined to judge) | 0.021 | 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".