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Record W3126246519 · doi:10.1016/j.jglr.2021.01.016

Shifting baselines and social license to operate: Challenges in communicating sea lamprey control

2021· article· en· W3126246519 on OpenAlexaffvenueabout
Marc Gaden, Cory O. Brant, Richard C. Stedman, Steven J. Cooke, Nathan Young, T. Bruce Lauber, Vivian M. Nguyen, Nancy A. Connelly, Barbara A. Knuth

Bibliographic record

VenueJournal of Great Lakes Research · 2021
Typearticle
Languageen
FieldEnvironmental Science
TopicFish Ecology and Management Studies
Canadian institutionsUniversity of OttawaCarleton University
Fundersnot available
KeywordsLicenseLampreyPetromyzonCommissionControl (management)HarmBusinessConventionEnvironmental planningFisheryPolitical sciencePublic relationsEnvironmental resource managementLawGeographyEnvironmental scienceComputer scienceBiology

Abstract

fetched live from OpenAlex

Sea lampreys (Petromyzon marinus) invaded the Great Lakes in the early twentieth century and caused considerable economic and ecological harm. People who fished the Great Lakes suffered crippling losses and successfully lobbied elected officials in Canada and the United States to create a sea lamprey control program which the Great Lakes Fishery Commission implements under the 1954 Convention on Great Lakes Fisheries. The control program relies on two primary methods: chemical lampricides and physical barriers. Sea lamprey control has been a tremendous success; although the urgency to act is apparent to certain publics and although control methods are deemed by professionals to be safe and effective, continued public advocacy for and acceptance of the control program is not ensured. Many people in the control program are concerned that the urgency to act is not commensurate with the risk sea lampreys continue to pose and that societal acceptance of the primary control methods could wane. This commentary reflects on issues of “shifting baselines” (changes in perceived risk) and the “social license to operate” (trust in authorities to make responsible decisions regarding current and planned control methods) and suggests a course to better understand these issues. Improved understanding of these issues will inform communication efforts for all involved in the control program. Moreover, the case examined here is potentially relevant and informative for other environmentally related actions where there may be erosion of the social license.

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)0.024
metaresearch head score (Gemma)0.047
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.062
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0240.047
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0010.001
Science and technology studies0.0120.033
Scholarly communication0.0080.011
Open science0.0050.005
Research integrity0.0230.017
Insufficient payload (model declined to judge)0.0020.001

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 head0.103
GPT teacher head0.356
Teacher spread0.253 · 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 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

Citations28
Published2021
Admission routes3
Has abstractyes

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