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Record W2913046222 · doi:10.1080/14634988.2018.1527136

Use of collaborative funding to implement the Remedial Action Plan for the St. Louis River Area of Concern, Minnesota, USA

2018· article· en· W2913046222 on OpenAlexaffabout
Nicholas French, Thijs Dekker, John H. Hartig

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2018
Typearticle
Languageen
FieldEnvironmental Science
TopicEnvironmental and Social Impact Assessments
Canadian institutionsBalsillie School of International Affairs
Fundersnot available
KeywordsRemedial actionAction planRemedial educationCommissionDredgingEnvironmental planningManagementPolitical scienceEnvironmental scienceLawEcology

Abstract

fetched live from OpenAlex

In the late 1800s and early 1900s, collaborative funding by some of the nation’s leading tycoons led to development of Duluth, Minnesota and the surrounding area. This included Andrew Carnegie, Jay Cooke, Andrew Mellon, J. P. Morgan and John D. Rockefeller, to name a few. This tremendous period of growth and expansion included major industrial developments, including grain, lumber, iron mining, manufacturing, rail, shipping and shipbuilding, and associated development of the frontier. Although critical to the development of a vital community, these activities took a toll through unchecked alteration of natural habitat and contamination of St. Louis River estuary sediments. These adverse legacy impacts, which occurred well before the establishment of our current environmental regulatory framework, became well recognized in 1985 when the International Joint Commission’s Great Lakes Water Quality Board identified the St. Louis River as an Area of Concern requiring the development and implementation of a remedial action plan to restore all impaired beneficial uses. This commitment to Remedial Action Plans was then codified in the 1987 Protocol to the U.S.-Canada Great Lakes Water Quality Agreement. The initial Stage 1 Remedial Action Plans for the St Louis River Area of Concern was completed in 1992 with the initial Stage 2 Remedial Action Plan completed in 1995, followed by periodic updates through 2012. However, these updates did not have budgets and action timelines necessary to secure the financial commitments to implement identified actions. Establishment of the Great Lakes Restoration Initiative in 2010 led to the 2013 Remedial Action Plan update (i.e. Stage 2 Remedial Action Plan) that included a business plan that identified specific actions, timelines, and budget estimates. Minnesota began implementing recommendations utilizing collaborative funding through a partnership approach. Ninety-nine percent of the actions identified in the Remedial Action Plan have been completed or are currently underway. Funding needs and sources have been clearly identified and the project is on track to complete major actions by 2020 and remove all beneficial use impairments and delist as an Area of Concern, dependent upon confirmation of use restoration, by 2025.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.202
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
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)0.0000.000

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 head0.111
GPT teacher head0.357
Teacher spread0.246 · 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 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
Published2018
Admission routes2
Has abstractyes

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