Adapting instruments and modifying statements: The confirmation method for the inventory and model for information sharing behavior using social media
Bibliographic record
Abstract
This study aims to confirm the information sharing behavior using social media scale and to validate every item and make it reliable as an inventory by using Exploratory Factor Analysis (EFA). The researcher adapted the measuring instruments for every latent construct from the literature and customized the items to suit this particular study. The study sent the revised questionnaire to 262 respondents in order to gather the pilot study data and able to get 163 filled ones as final data. The set of questionnaires consists of 66 items that assess the 6 constructs. Data is analyzed using SPSS AMOS Version 21.0. The results show that every construct achieved its Bartletts' Test of Sphericity < 0.05 and the measure of sampling adequacy by Kaiser-Meyer-Olkin (KMO) > 6.0 with the result of Information Sharing Behavior .000 and .871; Intention .000 and .782; Belief Expectancy .000 and .911; Attitude Influence .000 and .925; Readiness For Change .000 and .959; and Self-Efficacy .000 and .902. The entire item of the construct has exceeded the minimum limit of 0.7 reliability of Alpha Cronbach value to achieve the Internal Reliability. The new integrate model has been proposed due to this finding.
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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 | 0.047 | 0.140 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.001 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 0.002 |
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".