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Record W4408648885 · doi:10.1080/18366503.2025.2480951

Seafarers’ voices during the COVID-19 crisis and beyond: when excessive workload and related impacts become a turning point to quit

2025· article· en· W4408648885 on OpenAlexfundno aff
María Carrera-Arce, Raphaël Baumler, Bikram Singh Bhatia, Johan Hollander

Bibliographic record

VenueAustralian Journal of Maritime & Ocean Affairs · 2025
Typearticle
Languageen
FieldEngineering
TopicMaritime Navigation and Safety
Canadian institutionsnot available
FundersMinistry of Rural Affairs
KeywordsCoronavirus disease 2019 (COVID-19)Turning pointWorkload2019-20 coronavirus outbreakPoint (geometry)Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Tipping point (physics)PandemicPsychologyPolitical scienceEconomicsMedicineEngineeringVirologyMathematicsManagementAestheticsArtPeriod (music)

Abstract

fetched live from OpenAlex

The COVID-19 crisis locked seafarers at sea for extended periods, depriving them of the right to repatriation or shore leave, exposing them to extended contracts and working hours beyond reasonable limits, and impacting their health and mental well-being. Given the perceived ongoing degradation of seafarers’ conditions, the COVID-19 crisis seemed to have been an accelerator revealing structural deficiencies in the maritime sector. The study collected voices from the seas, analysing the aspects of workload and administrative burden and their impacts on seafarers’ well-being and retention. The research combined qualitative and quantitative methods. Seafarers (19) were interviewed, and a survey (3,959 responses) provided additional datasets. The research revealed increasing dissatisfaction with working and living conditions and pessimism among seafarers about improvements. Excessive workload, work stress and pressure exacerbated during the pandemic and for some became decisive to quit the profession. The chronic increase in workload, including paperwork, during the COVID-19 pandemic has significantly contributed to work discontent among seafarers. The increased work pressure and bureaucracy have made life at sea less acceptable for seafarers, accentuating the retention problem in the sector. The maritime sector risks losing skilled professionals if these structural deficiencies are not addressed.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.578
Threshold uncertainty score0.951

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.008
GPT teacher head0.249
Teacher spread0.241 · 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
Published2025
Admission routes1
Has abstractyes

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