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Record W2055638701 · doi:10.5558/tfc81398-3

Participatory requirements in forest management planning in Eastern Canada: A temporal and interprovincial perspective

2005· article· en· W2055638701 on OpenAlexaffvenueabout
Nicolas Lecomte, Catherine Martineau-Delisle, Solange Nadeau

Bibliographic record

VenueThe Forestry Chronicle · 2005
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsCanadian Forest ServiceUniversité LavalUniversité du Québec en Abitibi-TémiscamingueNatural Sciences and Engineering Research Council of CanadaUniversité du Québec à MontréalCentre Technologique des Résidus Industriels
Fundersnot available
KeywordsCitizen journalismPublic participationParticipatory managementSustainable forest managementPerspective (graphical)Participatory planningEnvironmental resource managementProcess (computing)Environmental planningForest managementSustainable managementBusinessParticipatory GISGeographyPolitical sciencePublic administrationSustainabilityForestryComputer scienceEconomicsEcologyManagement

Abstract

fetched live from OpenAlex

With the introduction of the concept of sustainable forest management, the practice of public participation has become omnipresent. This study focuses on provincial participatory requirements in forest management planning (FMP). A comparative framework composed of four participatory process attributes (power, moment of participation, learning/interaction, and procedure) was used to obtain a temporal and interprovincial perspective of Quebec's new participatory process. Our results indicate that with respect to past processes Quebec's current approach allows certain stakeholders, but not the general public, to have more access to FMP. Comparatively, Ontario and Newfoundland have implemented different, clearly stated, approaches that involve the general public at numerous stages of FMP. Future research should concentrate on how these participatory requirements are implemented and on the public satisfaction with regard to this implementation. Key words: public participation, forest management planning, descriptive framework, Canada, Quebec, 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)0.005
metaresearch head score (Gemma)0.007
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 score0.144
Threshold uncertainty score0.993

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.005
Science and technology studies0.0120.011
Scholarly communication0.0060.002
Open science0.0010.002
Research integrity0.0010.001
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 head0.025
GPT teacher head0.277
Teacher spread0.253 · 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

Citations13
Published2005
Admission routes3
Has abstractyes

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Same venueThe Forestry ChronicleSame topicForest Management and PolicyFrench-language works237,207