An empirical study into the effect of the digital divide on the intention to adopt e-government
Bibliographic record
Abstract
This study investigated the relationship between the digital gap and the intention of Jordanians towards e-government usage. It focused on three components of the digital divide namely access, skills, and innovativeness. In addition, the research investigated how socio-demographic factors influence this connection. Data comprised 620 valid replies to questionnaires issued to 700 Jordanian citizens aged 22 and older who resided in urban and rural areas. Statistical Package for the Social Sciences (SPSS) version 26 and Analysis of Moment Structures (AMOS) version 24 were employed in data analyses and hypotheses testing. The results showed that all three aspects of the digital divide had a significant influence (access, skills, and innovativeness) on the intent of Jordanian citizens to utilize e-government, and the dimension of access imparted the strongest impact, followed by the dimension of skills and then the dimension of innovativeness. Additionally, it was discovered that gender, age, and education were the socio-demographic factors that could weaken the impact of the digital divide on the intentions of user to access e-government services. Contrariwise, the factor of income did not show a similar impact. Furthermore, perceived security significantly impacted the propensity towards e-government usage. Trust played a significant role in mediating the link between perceived security and the intention to engage in e-government.
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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 | 0.006 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.004 | 0.001 |
| 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".