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Record W2061376121 · doi:10.5558/tfc84478-4

One hundred years of forestry education at UNB (1908–2008)

2008· article· en· W2061376121 on OpenAlexaffvenueabout
Glen A Jordan, G. R. Powell

Bibliographic record

VenueThe Forestry Chronicle · 2008
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsUniversity of New Brunswick
Fundersnot available
KeywordsBachelorForestryGraduation (instrument)GeographyPolitical scienceCurriculumEngineeringArchaeology

Abstract

fetched live from OpenAlex

Some key events that have shaped forestry instruction at the University of New Brunswick (UNB) following introduction of a BScF degree programme in 1908 are recounted. These include building of the Forestry and Geology Building in 1931, creation of the Faculty of Forestry in 1947, the large influx of students following WWII, extension of the BScF programme to five years in 1952, introduction of options in 1963, addition of a BScFE degree programme in 1968 and subsequently creation of Forest Resources and Forest Engineering Departments within the Faculty, addition of the New Forestry Building in 1976, early adoption and subsequent emphasis on computer technology from 1971 onward, graduation of its first PhD student in 1985, development in 1988 of the Faculty's Tweeddale Centre in the Hugh John Flemming Forestry Complex adjacent the UNB Woodlot, a massive increase in enrolments throughout the late 1980s and 1990s followed by a significant decline, significant curriculum changes in 1993, disbanding of Departments and renaming of the Faculty in 1994 to the Faculty of Forestry and Environmental Management, the move in 2007 back to four-year degree programmes, and in 2008, introduction of a third bachelor's degree programme, Environment and Natural resources (BScENR). Key words: University of New Brunswick, Forestry Faculty, history, degrees, facilities, personnel, departments, programmes, Fredericton

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)0.001
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: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.288
Threshold uncertainty score0.573

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0040.001
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0390.007

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 head0.017
GPT teacher head0.239
Teacher spread0.222 · 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 designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2008
Admission routes3
Has abstractyes

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