The Deshkan Ziibi Conservation Impact Bond Project: On Conservation Finance, Decolonization, and Community-Based Participatory Research
Bibliographic record
Abstract
The Deshkan Ziibi Conservation Impact Bond (CIB) model was developed in Canada as a novel approach to conservation finance building on components of existing conservation funding models. The CIB model responds to the urgent need for piloting reconciliatory and cross-cultural ways of collaborating with Indigenous communities to diversify investment partnerships and redirect capital to conservation efforts that promote the regeneration of land and reciprocal and respectful relationships in southern Ontario. The CIB is a financial instrument that facilitates cross-cultural collaboration by providing a common goal amongst a diverse set of sectors, partners, and worldviews to promote healthy landscapes and empower relationships between people and ecosystems. By leveraging financial incentives, this model aims to engage partners who may not have otherwise been attracted to conservation efforts. By tying financial returns to impact metrics of holistic landscape health that incorporate Indigenous worldviews and values of nature, this innovative instrument seeks to contribute towards shifting the conservation finance paradigm more broadly by engaging in the ongoing process of decolonizing the financialization of nature.
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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 | 0.004 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.010 | 0.001 |
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".