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Record W2003837983 · doi:10.1068/a3429

The Potential and Limits of Progressive Neopluralism: A Comparative Study of Forest Politics in Coastal British Columbia and South East New South Wales during the 1990s

2002· article· en· W2003837983 on OpenAlexaboutno aff
Phil McManus

Bibliographic record

VenueEnvironment and Planning A Economy and Space · 2002
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsDemocracyCarrGovernment (linguistics)Political scienceSouth eastForest managementPublic administrationPolitical economyGeographySociologyEcologyLawForestryEthnology

Abstract

fetched live from OpenAlex

During the 1990s the management of forests in British Columbia (Canada) and New South Wales (Australia) underwent many changes. For most of the decade the governments in both of these political jurisdictions were more socially and environmentally aware than their immediate predecessors. They were, however, far short of what many environmental and social activists desired. The New Democratic Party in British Columbia, led to government by Mike Harcourt, and the Australian Labor Party in New South Wales led by Bob Carr, may both be described as ‘centre-left/light-green’ in their political persuasions. This paper develops the regulation approach to explore the achievements, the potential and the limitations of these governments in the area of forest politics. It is argued that these governments implicitly adopted a progressive neopluralist approach to forest politics and attempted to manage environmental conflict by securing the agreement of many diverse interest groups. The experience of these two governments raises questions about the potential and limitations not just of the particular governments, but of a progressive neopluralist political strategy to achieve sustainable forest management.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.045
Threshold uncertainty score0.326

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0030.006
Science and technology studies0.0130.007
Scholarly communication0.0060.001
Open science0.0010.003
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0030.000

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 head0.019
GPT teacher head0.210
Teacher spread0.191 · 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 designObservational
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

Citations27
Published2002
Admission routes1
Has abstractyes

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