Development of a Measure: Internet Behaviors Scale
Bibliographic record
Abstract
Background and aims: Previous studies had documented that Social Networking Sites (S.N.S) has pathological effect on its users. A multi dimension syndrome, called problematic Internet use (PIU), causing behavioral and cognitive symptoms, which results in negative impact on different aspects of life like social, professional or academic. Because of increased attention to PIU, some measure had been made, but they seem to be inadequate, due to new issue of the internet interactions. Therefore the necessity and importance of standard, valid and reliable tools to assess PIU and the related behaviors is clear. In a survey conducted by Morahan-Martin and Schumacher on differences between lonely and non-lonely in internet behaviors, “Internet Behaviors scale” was used. The paper was frequently cited as a source by different researchers, but no validity or reliability for that scale was reported. The scale evaluates the different aspects of internet behavior which seems to be a quite helpful tool for PIU assessment. Method: This survey presented results of a study that evaluate reliability and validity of “Internet Behaviors Scales” with Iranian university students. This questionnaire was completed by 156 volunteer students of Shiraz University. To assess reliability coefficient α and test retest method was conducted. To assess validity exploratory factor analysis and convergent and discriminant validity was conducted. Results: Factor Analysis indicated three dimensions of this scale: social aspects, negative impact and competency and convenience aspect. “The internet Behaviors Scale” as the results indicate showed acceptable reliability and validity with Iranian students. Discussion: The internet Behaviors Scale as the results indicated could be used as a standard scale (valid and reliable) to evaluate PIU and related behaviors. It is important that validity and reliability of this scale be measured by other means.
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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 | 0.004 | 0.012 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.002 | 0.001 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.011 | 0.004 |
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".