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Record W1514587714

Contested Conservations: Forestry and History in Nova Scotia

2012· article· en· W1514587714 on OpenAlexfundaboutno aff
Mark Leeming

Bibliographic record

VenueTSpace · 2012
Typearticle
Languageen
FieldEnvironmental Science
TopicForest Management and Policy
Canadian institutionsnot available
FundersSocial Sciences and Humanities Research Council of CanadaMcMaster University
KeywordsNova scotiaIdeologyKnightPolitical scienceNegotiationGovernment (linguistics)PoliticsForestryAgency (philosophy)PrestigeEconomyPublic administrationGeographySociologyEconomicsSocial scienceArchaeologyLaw
DOInot available

Abstract

fetched live from OpenAlex

Forest conservation in Nova Scotia found its institutional expression in the 1920s, long after the establishment of many other Canadian and leading global centres of conservation science. With several differing and competing conservation ideologies from which to choose, the provincial government loaned its support to British, European, American, and Canadian versions at various times. Three successive leaders of the province's main forestry agency—J.A. Knight, Otto Schierbeck, and Wilfrid Creighton—demonstrated quite different ideals of conservation, and equally different strategies for negotiating the politics of forestry, ranging from prickly independence to eager cooperation with rival power centres in the federal government, international agencies, and in industry. Each distinct approach dictated a set of policies that helped shape the forest and the forest industries of Nova Scotia. Contrary to the assumption that conservationists past and present approach more or less closely a single, ahistorical scientific norm, the account of policy vacillation in this essay illustrates the ideological content and historical contingency of forestry science.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
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)0.0050.001

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 head0.038
GPT teacher head0.286
Teacher spread0.248 · 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; both teacher heads agree on what is shown here.

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

Citations2
Published2012
Admission routes2
Has abstractyes

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