Industry 4.0 in shipping: Implications to seafarers' skills and training
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.
Bibliographic record
Abstract
Industry 4.0 entails the modernisation of work, which is likely to have an impact on individuals’ employment, training and skills in the foreseeable future. Current debates on future skills for maritime operations tend to focus on technology as a necessary requirement for workers to adapt to changes. This technology-centred approach can be controversial as technology cannot govern how humans work and how they choose their careers after graduating. This paper employs a career-focused perspective that addresses Industry 4.0 and digitalisation from individuals’ career development viewpoint, and discusses the potential implications of digitalisation and automation on individuals’ careers in the maritime industry. The paper contributes to the discussion of how Industry 4.0 and digitalisation have the potential to affect individuals’ skills and training, as well as their future career trajectories. The paper also scrutinises career structures for seafarers as well as possible socio-economic implications on future maritime careers, skills and training in the context of Industry 4.0. These issues are examined through the use of interview data from two empirical projects between 2007 and 2018 as well as a literature review on careers in the global labour market and on Industry 4.0. It concludes with a set of agendas highlighting potential shortage of career support systems for seafarers as well as the need for stakeholder engagement in shaping future maritime skills.
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Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it