In Perpetuity: Governance and Capacity Building of Local Land Trusts in Ontario
Bibliographic record
Abstract
This study examines the extent to which volunteer-run local land trusts in Ontario are governed in a manner that will allow them to protect valued ecosystems effectively in perpetuity. It also identifies needs and opportunities for building the capacities of land trusts as long term stewardship organizations. The primary academic contribution of this research is the identification of criteria for evaluating land trust governance and their ability to meet their conservation aims. The criteria are applied in a case study of the Niagara Land Trust, a local land trust in the process of incorporating. Specific recommendations are made to assist this organization to improve its operations. \n \nThe principal findings of this research are that some local land trusts have attained a level of governance which will allow them to protect land in perpetuity, but some land trusts have not. The failure of some land trusts could result in donors and government questioning the movement as a whole. Generally, the main gaps in capacity centre on weaknesses in financial sustainability, training/managing of volunteers, record-keeping, baseline inventories and continued monitoring, and the problem of requiring people to have specific professional skills in largely volunteer organizations. \n \nThe thesis concludes by offering specific suggestions to the Niagara Land Trust, the Ontario Land Trust Alliance and the Canadian Land Trust Alliance. Local land trusts have provided many communities with an attractive option for conserving land; strengthening the movement will ensure that this grassroots work can continue.
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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 | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.009 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| 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".