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Record W2420126920 · doi:10.1139/cjfr-2016-0207

The state of innovation in the British Columbia value-added wood products sector: the example of chain of custody certification

2016· article· en· W2420126920 on OpenAlexaffvenueabout
Haris R. Gilani, Robert Kozak, John L. Innes

Bibliographic record

VenueCanadian Journal of Forest Research · 2016
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicGlobal trade, sustainability, and social impact
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsCertificationBusinessProduct (mathematics)Value chainValue (mathematics)Added valueCertified woodMarketingWood industryIndustrial organizationSupply chainForestryManagementEconomicsMathematicsGeography

Abstract

fetched live from OpenAlex

This paper investigates the practices of the value-added wood products industry in British Columbia (BC) with respect to innovativeness using the results of an online survey. The survey employed an indirect self-evaluation scale to assess the propensity to create and (or) adopt new products, processes, and business systems. Using chain of custody certification as an example of business systems innovation, this study also investigated the attitudes of the value-added wood products manufacturers, who were already certified or who may become certified, towards innovation in this form. Results show that the respondents rated themselves as more innovative with respect to business systems innovation compared with product and process innovations. Overall, innovation levels were low in the BC value-added wood products sector, a result which was confirmed in the case of chain of custody certification.

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)0.002
metaresearch head score (Gemma)0.006
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: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.101
Threshold uncertainty score0.204

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.006
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0030.003
Scholarly communication0.0030.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.073
GPT teacher head0.297
Teacher spread0.225 · 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

Citations12
Published2016
Admission routes3
Has abstractyes

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