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Record W7005598727

The role of project-based impact assessment in considering the impacts of resource development related Arctic shipping

2022· dissertation· en· W7005598727 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2022
Typedissertation
Languageen
FieldAgricultural and Biological Sciences
TopicDate Palm Research Studies
Canadian institutionsnot available
Fundersnot available
KeywordsScope (computer science)Resource (disambiguation)Work (physics)Impact assessmentArcticEnvironmental impact assessmentThe arctic
DOInot available

Abstract

fetched live from OpenAlex

Transportation by sea is the main method for the movement of goods in the Arctic. With longer ice-free periods, and new technology, the increases in ship traffic experienced over the past few decades are expected to continue. Resource development projects are an important source of ongoing increases in regional shipping. My thesis attempts to understand the potential of Nunavut’s impact assessment (IA) framework to meaningfully identify and address the impacts associated with project related shipping. To achieve this purpose, I conducted a literature review and document review of several recent IAs in Nunavut. To enhance the data collected through the document review, I carried out interviews with experts and participants of the IAs studied. The results of my work indicate that IA in Nunavut routinely includes shipping impacts within the scope of assessment, and many shipping related concerns have been documented throughout IA proceedings. Further, my findings indicate that IA can influence project shipping through mitigation measures and consultation requirements. However, my data also reveal that important factors serve to limit the reach of project-IA when attempting to impose conditions on project shipping that exceed the requirements of regional shipping regulations. One example of this relates to the lack of spill response capacity and the implications of this for the Canadian Arctic. Nonetheless, my findings demonstrate that IA is an important forum for resource management in Nunavut, and that IA offers critical opportunities for shipping impacts to be addressed on a project basis moving forward.

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 score0.475
Threshold uncertainty score0.990

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.000
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 head0.022
GPT teacher head0.258
Teacher spread0.236 · 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

Citations0
Published2022
Admission routes1
Has abstractyes

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