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Record W3037217445 · doi:10.20381/0hgb-7h91

Shipping Trends in Tallurutiup Imanga (Lancaster Sound), Nunavut from 1990 to 2018 Description

2020· article· en· W3037217445 on OpenAlexaboutno aff
Zuzanna Kochanowicz, Jackie Dawson, Olivia Mussells

Bibliographic record

VenueuO Research (University of Ottawa) · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsnot available
Fundersnot available
KeywordsSound (geography)GeographyGeologyOceanography

Abstract

fetched live from OpenAlex

This study involved in-depth examination of the past and present shipping activities across Tallurutiup Imanga (Lancaster Sound), Nunavut, Canada from 1990 to 2018. Marine traffic increased dramatically over the 29-year period examined in the study. The total distance travelled by all vessels almost tripled between 1990 (51,584 km) and 2018 (142,111 km), with a notably steep increase in distance between 2009 (61,783 km) and 2014 (104,098 km); furthermore, the distance travelled by some vessel types increased considerably more than others (e.g., pleasure crafts, passenger ships, and general cargo). The spatial concentration of ship traffic in Tallurutiup Imanga has been relatively consistent over time, with most vessels travelling in the middle of the channel as well as branching off to the five surrounding communities and to the Mary River Mine which is accessed through Milne Inlet. However, some changes in intensity and distribution are evident within certain vessel types. Notably, pleasure crafts and passenger ships are substantially more concentrated in routes on the way to communities as well as around Beechy Island on the southwestern tip of Devon Island. The overall spatial change in vessel traffic within 50 kilometres of each of the five communities varies quite a bit; however, it is noteworthy that the community of Pond Inlet, a community in the heart of the Tallurutiup Imanga region, has seen the greatest increase in vessel traffic compared to Canadian Arctic communities across all of Inuit Nunangat.

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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.399
Threshold uncertainty score0.986

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 studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0010.000

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 head0.181
GPT teacher head0.367
Teacher spread0.186 · 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

Citations3
Published2020
Admission routes1
Has abstractyes

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