The Satisfaction of the Fishermen in the South China Sea With the Summer Fishing Moratorium System and Its Influencing Factors
Bibliographic record
Abstract
This study investigated the satisfaction of fishermen with the summer fishing moratorium system in the three provinces of the South China Sea through a questionnaire survey and explored the degree of its influencing factors. A multistage random sampling method was used to issue questionnaires to fishermen involved in the summer fishing moratorium. A total of 258 valid questionnaires were collected, and the factors were analyzed them using the factor analysis method by SPSS 23.0 software. The results showed that the variance contribution rate of the first five factors reached 61.859%, and the 11 factors that have potential commonality in influencing fishermen’s satisfaction with the fishing moratorium can be summarized and classified into five more significant factors, such as “economic income during fishing moratorium (16.396),” “illegal fishing boat (12.095),” “fishing moratorium time (12.012),” “law enforcement credibility (11.853),” and “summer fishing moratorium effect (9.503).” According to the factor score calculation, the fishermen’s satisfaction with the fishing moratorium was F = 3.53, and the overall satisfaction was relatively high. This study reveals the satisfaction degree of the fishermen in the South China Sea with the summer fishing moratorium system and its influencing factors, which can provide a basis for improving the summer fishing moratorium system and ensuring the lives of fishermen.
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How this classification was reachedexpand
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 | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".