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Record W2031867731 · doi:10.5558/tfc84481-4

Management of New Brunswick's Crown forest during the twentieth century

2008· article· en· W2031867731 on OpenAlexaffvenueabout
Nancy D. Holloway, Glen A Jordan, Burtt M Smith

Bibliographic record

VenueThe Forestry Chronicle · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsGovernment of New BrunswickUniversity of New Brunswick
Fundersnot available
KeywordsForestryCrown (dentistry)Forest managementCommunity forestryPosition (finance)GeographyPolitical scienceBusiness

Abstract

fetched live from OpenAlex

A condensed history of forestry and forest management in New Brunswick's Crown Forest during the 20th century is presented. It begins with a description of the advanced state of forest management in New Brunswick today. The description provides a sharp contrast to the subsequent detailing of forestry operations, and lack of forest management, that characterized the early decades of the 20th century. A gradual improvement followed, as professional forestry education and technology combined to elevate forestry practice. Next examined is forestry practice and its change across several distinct periods: the inter-wars period (1914–1938), WWII and aftermath (1939–1957), two decades of profound change (1958–1980), and the modern era (1981–2005). It is concluded that a few key events and individuals explain the gradual evolution of forestry in New Brunswick from controlled exploitation to sustainable management. Also suggested is that the Faculty of Forestry and Environmental Management at the University of New Brunswick must continue to attract the brightest and best to its forestry programmes, if New Brunswick is to maintain its leadership position in management of public forests. Key words: forest management, history, Province of New Brunswick, technological advances, forestry practice, key personnel, Crown Lands and Forests Act

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)0.000
metaresearch head score (Gemma)0.001
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 score0.079
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.004
Science and technology studies0.0040.002
Scholarly communication0.0020.001
Open science0.0010.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.011
GPT teacher head0.221
Teacher spread0.210 · 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

Citations3
Published2008
Admission routes3
Has abstractyes

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