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Record W4401130598 · doi:10.18280/ijsdp.190724

Passenger Attitudes and Waste Management on Ships

2024· article· en· W4401130598 on OpenAlexvenueno aff
Kuncowati Kuncowati

Bibliographic record

VenueInternational Journal of Sustainable Development and Planning · 2024
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessWaste managementEnvironmental planningEnvironmental scienceTransport engineeringEngineering

Abstract

fetched live from OpenAlex

The problem of waste management on passenger ships is often observed due to the continuous disposal of rubbish on the deck and into the sea irrespective of the bin provided on each side of the railings.This leads to the collection and sorting of various waste by the ship crew, including plastic, paper, food, cans, and coating materials, which impacts safety management, as well as environmental pollution.Passengers are also not required to commonly have competency and proficiency in ship waste management.Therefore, this study aimed to analyze the effects of passenger attitudes on ship waste management, using a Structural Equation Modeling-Partial Least Squares (SEM-PLS) and 160 participants in Tanjung Perak Port, Indonesia.The results showed that environmental concerns, as well as passenger perceptions and attitudes strongly influenced solid waste management on ships.

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)0.000
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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.823
Threshold uncertainty score0.267

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.011
GPT teacher head0.249
Teacher spread0.238 · 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 designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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