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Record W1964054482 · doi:10.1016/s1449-4035(07)70101-7

The Future of Non-State Authority on Canadian Staples Industries: Assessing the Emergence of Forest Certification

2007· article· en· W1964054482 on OpenAlexaboutno aff
Benjamin Cashore, Graeme Auld, James S. Lawson, Deanna Newsom

Bibliographic record

VenuePolicy and Society · 2007
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsnot available
Fundersnot available
KeywordsState (computer science)Corporate governanceCertificationState forestFunction (biology)Certified woodPublic administrationEconomyBusinessPolitical scienceEconomicsForest managementFinanceForestryManagementGeography

Abstract

fetched live from OpenAlex

Abstract Virtually all of the literature on Canada as a “staples state” has focused on two related topics: the impact of a historically staples-based economy on the development of the Canadian state’s structure, function and policy outcomes; and, given these historical influences, the ability and capacity state officials might have to veer Canada off this “hinterland” pathway by facilitating a more diversified Canadian economy less dependent on the US “metropole”. While these foci are important, the dramatic arrival in the 1990s of Non-State Market Driven (NSMD) governance systems that focus largely on regulating staples extracting sectors such as forestry, fisheries, and mining, has raised important new questions for students of the staples state.

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)0.005
metaresearch head score (Gemma)0.024
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.932
Threshold uncertainty score0.490

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.024
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0040.004
Science and technology studies0.0040.004
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0000.001
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 head0.032
GPT teacher head0.317
Teacher spread0.285 · 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 designQualitative
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

Citations9
Published2007
Admission routes1
Has abstractyes

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