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Record W2084203382 · doi:10.5558/tfc85538-4

Estimation des retombées économiques directes engendrées par le réseau de création de valeur de la filière bois de feuillus durs au Québec

2009· article· en· W2084203382 on OpenAlexaffvenueabout
Mathieu Trudelle, Nancy Gélinas, Robert Beauregard

Bibliographic record

VenueThe Forestry Chronicle · 2009
Typearticle
Languageen
FieldEngineering
TopicForest Biomass Utilization and Management
Canadian institutionsUniversité Laval
Fundersnot available
KeywordsHardwoodDeciduousSoftwoodForestryProduction (economics)Agricultural scienceMathematicsEconomic analysisGeographyAgricultural economicsHumanitiesEconomicsBotanyEngineeringPulp and paper industryArtEnvironmental scienceBiologyMicroeconomics

Abstract

fetched live from OpenAlex

Deciduous hardwood species represent more than 17% of the total fibre used in primary wood processing mills in Quebec. However, economic outcomes from primary and secondary hardwood processing are not well documented. Meanwhile, many questions arise regarding the growing difficulty of good access to the fibre in both quantity and quality. The main objective of this study is to define the hardwood network. To do so, we have to quantify the economic outcomes by developing a method of evaluation of the outcomes induced by the industries of 2 nd and 3 rd transformation, compare that network with the softwood network and then, finally, make a sensitivity analysis of these outcomes when facing variation in the level of exports and the average sale price. The results show that in 2002, the value of production of the hardwood processing industry, all levels combined, was 2.3 billion dollars. The presence of a 2 nd and 3 rd transformation industry can allow an increase of more than double the value of production. Hardwood sawmills generate direct economic outcomes similar to the softwood industry but at a smaller production scale. The sensitivity analysis showed that a decrease of 5% in exports of the 1 st transformation products would generate a growth of 3% of the value of the total deliveries and increase the total number of employees of the 2 nd and 3 rd transformation industry by 9%. Key words: deciduous hardwood, first and second transformation, exports, direct economic outcome, employment

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 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: Simulation or modeling · Consensus signal: Simulation or modeling
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.310
Threshold uncertainty score0.999

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)0.0000.000

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 head0.008
GPT teacher head0.226
Teacher spread0.217 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designSimulation or modeling
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

Citations1
Published2009
Admission routes3
Has abstractyes

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