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Record W74875765 · doi:10.3138/jcs.37.2.130

Fumes, Forests and Further Studies: Environmental Science and Policy Inaction in Ontario

2002· article· en· W74875765 on OpenAlexvenueaboutno aff
Don Munton

Bibliographic record

VenueJournal of Canadian Studies · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicCanadian Identity and History
Canadian institutionsnot available
Fundersnot available
KeywordsEnvironmental policyScience policyScientific evidencePublic policyAsideSet-asidePolitical scienceEnvironmental ethicsNatural resource economicsPublic administrationEconomicsLawEcology

Abstract

fetched live from OpenAlex

Conclusions about the role of scientific knowledge in shaping environmental policy, such as the acid rain case, have tended to focus on contemporary events and to suggest the responsiveness of governments to scientific research. This article looks instead at the scientific evidence of acidification problems in Ontario prior to the 1970s, indeed back to the 1920s, and considers the lack of governmental response to a mounting body of scientific evidence over the twentieth century regarding forest damage from sulphur fumes. Until the 1970s the evidence was consistently disregarded or set aside by policy-makers intent on ensuring the Ontario smelter industry continue in unrestricted fashion. This case study reveals how science, rather than be an effective influence for such change, can be ignored in the making of public policy and how further research can displace policy change.

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)0.001
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: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.606
Threshold uncertainty score0.992

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.039
GPT teacher head0.266
Teacher spread0.227 · 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 designQualitative
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

Citations5
Published2002
Admission routes2
Has abstractyes

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