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Record W4377079958 · doi:10.1139/facets-2022-0095

Laws matter: a foundational approach to biodiversity conservation in Canada

2023· article· en· W4377079958 on OpenAlexaffvenueabout
Trevor Swerdfager, Andrea Olive

Bibliographic record

VenueFACETS · 2023
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental Conservation and Management
Canadian institutionsGeneral Electric (Canada)University of TorontoUniversity of Waterloo
Fundersnot available
KeywordsLegislatureConservation psychologyBiodiversity conservationConservation lawBiodiversityCorporate governancePerspective (graphical)Political scienceConservation biologyEnvironmental lawSet (abstract data type)Law and economicsEnvironmental resource managementEnvironmental ethicsBusinessLawEcologyEconomicsBiologyComputer science

Abstract

fetched live from OpenAlex

This perspective essay examines the role of conservation law in contributing to biodiversity decline by exploring how current conservation laws exacerbate the challenges Canada faces. We contend that there are three intertwined foundation-setting functions of conservation law: they codify priorities and values, define and influence acceptable conservation behaviour, and drive the establishment of the institutions, programs, and governance arrangements of today’s conservation regime. We describe these functions and then assess whether conservation laws in Canada are adequately fulfilling the functions. We find that the federal conservation law regime is sub-optimal and likely incapable of halting and reversing the negative biodiversity trends. Based on this, we suggest a set of conservation legislative principles capable of catalyzing change and supporting the transition to a more sustainable conservation future.

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 imitation

Not 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.

metaresearch head score (Codex)0.003
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.143
Threshold uncertainty score0.994

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0170.023
Scholarly communication0.0130.004
Open science0.0030.003
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0040.000

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 head0.018
GPT teacher head0.190
Teacher spread0.172 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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

Citations4
Published2023
Admission routes3
Has abstractyes

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