Narrative Study on Successful Career Transition Based on Experiences of Chinese Vocational College Maritime Students
Bibliographic record
Abstract
Chinese vocational college maritime graduates play a crucial role in the maritime field. They operate ship equipment, ensure maritime safety, and provide important support in achieving the goal of China becoming a maritime power. Therefore, paying attention to their career development is of significant importance. This study adopted a narrative research approach and aimed to delve into the inner journey of successful career transition among 12 Chinese vocational college maritime graduates. It was conducted through semi structured interviews to gain a comprehensive understanding of their experiences. The research findings indicate the interviewees identified several challenging factors associated with the maritime profession. These factors include monotonous and oppressive job tasks, high work pressure, confined spaces on ships, fixed and inflexible salaries, limited career advancement opportunities, a sense of disconnection from society, difficulties making friends, challenges achieving work–life balance, and limited prospects for career growth. These factors contributed to a subjective sense of professional dissatisfaction among them. However, once they transitioned to land-based jobs, they achieved subjective professional success. This can mainly be attributed to the fact that land-based jobs allow them to take care of their families, pursue a more independent lifestyle, maintain social connections, and lead a stable life. Based on the research findings, it is recommended ship companies and society as a whole pay attention to the career development of maritime students and improve the working environment in the maritime industry. This is necessary to meet their needs for balancing family responsibilities, pursuing a more independent lifestyle, and maintaining social connections. By addressing these aspects, it will help facilitate subjective professional success among maritime students.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.012 | 0.004 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.003 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".