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Record W1878772257

Labour and the Environment: Five Stories from New Brunswick Since the 1970s

2014· article· en· W1878772257 on OpenAlexaboutno aff
Joan McFarland

Bibliographic record

VenueÉrudit (Université de Montréal) · 2014
Typearticle
Languageen
FieldEnvironmental Science
TopicAmerican Environmental and Regional History
Canadian institutionsnot available
Fundersnot available
KeywordsAllianceGovernment (linguistics)MillPolitical scienceWork (physics)SAINTEconomic historyEngineeringLawHistory
DOInot available

Abstract

fetched live from OpenAlex

A clip circulating on the Internet of the announcement of new investment in Irving Pulp & Paper shows Jerry Dias, the national president of Unifor, at the mill in Saint John, New Brunswick thanking Jim Irving, President of J.D. Irving Ltd., and the Irving workers for a job well done in getting a new forestry plan in NB.1 The event, with Premier David Alward in attendance, took place just after the New Brunswick government’s 12 March 2014 announcement of the plan. The latter, which increases the cut on the province’s Crown lands, has been emphatically denounced by environmentalists. This alliance between labour and industry, by ignoring environmentalists’ concerns, is an aberration. In the past 40-plus years, and at present in other sectors in New Brunswick, labour has a history of alliance-building and significant cooperation with environmentalists. This is not just an issue in New Brunswick. Throughout North America and much of the world, the question of whether the labour and environmental movements can work together has been a central one.2 Government and industry would have us believe that there is an inherent conflict between jobs and the environment. Yet many have argued that juxtaposing “jobs versus the environment” is a false choice and that the environmental and labour movements can work in alliances to build a more sustainable world. Indeed, my

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: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.502
Threshold uncertainty score0.971

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 studies0.0010.003
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.001

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 head0.002
GPT teacher head0.125
Teacher spread0.123 · 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 designNot applicable
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

Citations4
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueÉrudit (Université de Montréal)Same topicAmerican Environmental and Regional HistoryFrench-language works237,207