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Record W2526825918 · doi:10.1017/s0032247416000565

Management challenges for the fastest growing marine shipping sector in Arctic Canada: pleasure crafts

2016· article· en· W2526825918 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.
fundA Canadian funder is recorded on the work.
aboutThe title or abstract carries a Canadian signal from the geographic lexicon.

Bibliographic record

VenuePolar Record · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicArctic and Russian Policy Studies
Canadian institutionsUniversity of OttawaLakehead University
FundersTransport Canada
KeywordsTourismCraftVisitor patternStakeholderArcticPleasureBusinessGovernment (linguistics)Environmental resource managementEnvironmental planningGeographyPolitical sciencePublic relationsEcologyEnvironmental science

Abstract

fetched live from OpenAlex

ABSTRACT Changing environmental conditions in the Canadian Arctic are associated with an increase in marine tourism. A substantial decline in the extent of ice coverage in the summer season has resulted in greater accessibility for all categories of ships, and the tourism sector has been quick to respond to new opportunities. This increase in vessel traffic has raised significant issues for management, and particular concerns about the pleasure craft (non-commercial tourism) sector. This paper reports on research aimed at identifying change in the pleasure craft sector in Canadian Arctic waters since 1990; exploring management concerns held by stakeholders regarding changes in the sector; and, providing recommendations for government stakeholders. The paper is based on material gathered through an examination of existing data sources and stakeholder interviews ( n = 22). Analysis was aimed at understanding the rapid development of the sector and potential management strategies, including research needs. Analysis reveals a dramatic increase in annual vessel numbers, particularly from 2010 onwards. Management concerns of interviewees relate to implications of this growth in four areas: visitor behaviour; services, facilities and infrastructure; control; and, planning and development. The paper concludes by describing recommendations in the areas of research needs, regulation, and strategic development.

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.

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: Other design · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.917
Threshold uncertainty score0.421

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 studies0.0010.000
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 head0.047
GPT teacher head0.275
Teacher spread0.228 · 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