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Record W2106200993 · doi:10.1080/14634988.2012.659142

Environmental rejuvenation of the Gulf by compensation and restoration

2012· article· en· W2106200993 on OpenAlexaff
Andrew Price, Michael Donlan, Charles Sheppard, M. Munawar

Bibliographic record

VenueAquatic Ecosystem Health & Management · 2012
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicEconomic and Environmental Valuation
Canadian institutionsFisheries and Oceans Canada
FundersKuwait Institute for Scientific Research
KeywordsInterimEcosystemMarine ecosystemEcosystem servicesEnvironmental scienceEnvironmental restorationEnvironmental resource managementResource (disambiguation)Environmental protectionEcologyGeography

Abstract

fetched live from OpenAlex

The Gulf is considered to be a young sea in decline, with poor prognosis for continuing production of abundant natural resources. We compare and contrast ‘monetary’ and ‘environmental’ compensation as mechanisms for addressing ecosystem damage in the Gulf. The 1992 International Oil Pollution Compensation Conventions settle claims financially, but only for certain categories of oil spills. For example, aside from inherent difficulties of valuing ecosystem services and their losses, ecological damage from the time of injury to recovery (interim losses) is not compensated. Another approach involves reimbursement for environmental action/projects to restore affected resources and offset impacts until recovery. In habitat equivalency analysis, mitigation requirements are calculated from the type(s), severity, duration and extent of resource impacts. This approach was utilized to resolve several claims for damage from the 1991 Gulf War oil spill. Various compensatory projects resulted, including direct oil spill remediation and other environmental projects such as the establishment of ≥1 protected area (x ha for y years). Besides compensation, in this paper we advocate setting threshold levels for the protection of different coastal and marine ecosystems. This could be achieved by a proportion (c. 30%) of every major ecosystem becoming fully protected, through an expanded regional protected area network.

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 score0.114
Threshold uncertainty score0.370

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 head0.051
GPT teacher head0.217
Teacher spread0.166 · 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

Citations4
Published2012
Admission routes1
Has abstractyes

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