Influence of Behavioral Factors on Mobile Phone Usage among Fishermen: The Case of Pangkor Island Fishermen
Bibliographic record
Abstract
The swift evolution of mobile phone technology has benefited various groups within communities. Fishermen, as one of the important groups, particularly in terms of their role in ensuring the nation’s food security, rely on mobile phones to conduct their fishing routines. While there is an abundance of studies that explore factors influencing mobile phone usage in various groups of communities, less interest has been placed on mobile phone usage among fishermen. This has driven the current study to its focal objective, which is to determine the behavioral factors that influence the usage of mobile phones among fishermen. This study is quantitative, and surveys a total of 250 registered fishermen from Pangkor Island – one of the main fishing areas in Perak. The results demonstrate that most of the fishermen use mobile phones for safety and communication purposes. In addition, due to a number of problems, fishermen are found to use advanced mobile phone applications such as 3G, Internet and GPS at a minimal level. Further analysis confirms that four behavioral factors, namely performance expectancy, effort expectancy, behavioral intention and social influence, have positive and significant correlations with mobile phone usage.
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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 | 0.002 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.002 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 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".