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Record W3213112594 · doi:10.5206/101121ipib

The Deshkan Ziibi Conservation Impact Bond Project: On Conservation Finance, Decolonization, and Community-Based Participatory Research

2021· book· en· W3213112594 on OpenAlexaboutno aff

Bibliographic record

VenueWestern Libraries eBooks · 2021
Typebook
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
Fundersnot available
KeywordsIndigenousFinancializationIncentiveMarine conservationBusinessFinanceEnvironmental resource managementPolitical scienceEnvironmental planningEconomicsGeographyEcology

Abstract

fetched live from OpenAlex

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.

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.615
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0030.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.002
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.286
GPT teacher head0.346
Teacher spread0.060 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

Study designNot applicable
Domainnot available
GenreOther

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".

Quick stats

Citations3
Published2021
Admission routes1
Has abstractyes

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