An Institutional Analysis of the Portage Community Pasture as a Common Property Resources
Bibliographic record
Abstract
"The Canadian community pastures Program (CPP) began in 1939 under the Prairie Farm \nRehabilitation Act to mitigate the effects of severe drought in the prairies through \nconversion of submarginal land into shared pasture lands managed by the federal \ngovernment. In 2012, the Canadian federal government withdrew their involvement from \nthe CPP and transferred the program to their provincial counterparts. The Portage \ncommunity pasture (PCP) in Manitoba formed its own association, the Portage Pasture \nAssociation (PPA), and is operating by and for its members. This thesis investigates the \ncurrent state of the PCP through identifying: i) governance structures used for decision \nmaking and community pasture operations; ii) perspectives of commons users and \nmanagers on changing governance structures; and, iii) long-term sustainability and equity \nin governance of the PCP. An institutional analysis using Elinor Ostrom’s principles for \nsustainable common property resources was performed. Eight participants were \ninterviewed, then transcripts and documents were analyzed for themes and trends using \nNVivo 12.0 Plus. Ostrom’s framework was applicable to the community pastures context. \nThe PPA satisfies Ostrom’s principles and they are especially strong in rules matching \nthe local context, graduated sanctions, conflict resolution mechanisms, and local \ninstitutions being respected by external authorities. The PPA is perceived as sustainable \nby its users."
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 | 0.005 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.013 | 0.013 |
| Scholarly communication | 0.006 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 0.000 |
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".