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Record W3044485770 · doi:10.4236/nr.2020.117017

Assessment of a Public Participation Tool by Experts: A Case Study of Quebec, Canada

2020· article· en· W3044485770 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenueNatural Resources · 2020
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversité Laval
FundersGénome QuébecGenome Canada
KeywordsPolitical scienceEnvironmental planningGeography

Abstract

fetched live from OpenAlex

In theory, sustainable forest management (SFM) puts public participation at the epicenter of the decision-making process. However, in reality, the situation is different. The growing importance of public participation seems essential for the implementation of sustainable forest management. The aim of this study is to assess the implementation of a theoretical concept closely related to SFM, integrated land and resource management (ILRM). This Canadian concept aims to integrate many forest functions using participatory tools. Using semi-structured interviews with experts, we clarify our theoretical concept and adapt it to reality. Our results show that better communication between stakeholders is necessary. It is also important to increase the flexibility of the timber harvest system and adapted forest zoning should be considered. A new concept, the forest culture, seems to be a key element that needs to be considered upstream of forest management. A new definition of ILRM is proposed in order to better reach social values.

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.

Full frame distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.129
Threshold uncertainty score0.762

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.021
GPT teacher head0.283
Teacher spread0.261 · 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