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Record W4383558580 · doi:10.51325/ijbeg.v6i1.120

The Spread of Social Inclusion in the Maritime Industry: A Social Study

2023· article· en· W4383558580 on OpenAlexaffabout
Lucie Sislian, Anicia Jaegler

Bibliographic record

VenueInternational Journal of Business Ethics and Governance · 2023
Typearticle
Languageen
FieldEngineering
TopicMaritime Ports and Logistics
Canadian institutionsCégep Marie-Victorin
Fundersnot available
KeywordsPort (circuit theory)Inclusion (mineral)Diversity (politics)Sustainable developmentStructural equation modelingMaritime industryBusinessPublic relationsSociologyEngineeringPolitical scienceComputer scienceSocial scienceCommerce

Abstract

fetched live from OpenAlex

This paper presents a social study on the maritime port of Montreal investigating the spread of social inclusion in the maritime industry. We used both qualitative and quantitative methods, including structural equation modeling to answer the research questions. Our findings show that the spread of social inclusion was significant in the port in terms of workplace diversity and inclusion, the workplace environment, and the port’s responsibility toward society. These findings highlight specific factors that are currently being overlooked and thus require greater industry collaboration. The proposed framework also serves as a tool for a single maritime port to self-assess its current stage of sustainable development, with implications for future social-inclusion implementation strategies.

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)0.002
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 score0.854
Threshold uncertainty score0.412

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
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 integrity0.0000.001
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 head0.037
GPT teacher head0.306
Teacher spread0.269 · 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
Published2023
Admission routes2
Has abstractyes

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