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Record W7097198217

1 STRENGTHENING THE CONSERVATION OF BIODIVERSITY: REFORMING ONTARIO=S PROVINCIAL PARKS ACT

2016· article· en· W7097198217 on OpenAlexaboutno aff

Bibliographic record

Venuenot available
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsnot available
Fundersnot available
KeywordsLegislatureLegislationMandateAccountabilityResource (disambiguation)Resource management (computing)Public participationDiversity (politics)
DOInot available

Abstract

fetched live from OpenAlex

The management of existing provincial parks in Ontario, and the creation of new ones, is legislatively governed by the Provincial Parks Act. This evaluation of park legislation assesses its capability of managing complex ecological realities, fostering adequate planning, ensuring proper implementation, and generating public involvement. The increasing size of the parks system and the biological diversity of Ontario represent the ideas of change and complexity in resource and environmental management. This paper suggests that the Provincial Parks Act must be reformed to address these changes and complexities. The mandate and legislative framework of the parks system must be redesigned to promote a proactive approach in conserving the biodiversity of Ontario. Reform is needed in the planning of parks and their management. Public participation and accountability must also be assured. Similar reform in the management of protected areas has occurred at the level of the federal parks system. This paper discusses important proposals for legislative change to Ontario=s Provincial Parks Act, specifically:(i) the recognition of biodiversity conservation as a primary goal; (ii) the need for management plans for each park; and (iii) the requirement for an open consultative planning process.

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)0.004
metaresearch head score (Gemma)0.011
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.082
Threshold uncertainty score0.595

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.003
Scholarly communication0.0050.001
Open science0.0020.002
Research integrity0.0020.002
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 head0.014
GPT teacher head0.223
Teacher spread0.209 · 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

Citations0
Published2016
Admission routes1
Has abstractyes

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