Successful Community Municipal Portal Diffusion: Internal Government Factors and Individual Perceptions
Bibliographic record
Abstract
This paper presents findings and research directions of an in-progress study examining the factors affecting successful community municipal portal diffusion. Several community municipal portal sites in the Province of Ontario, Canada are being investigated via questionnaires sent to portal administrators at six portal sites, and web surveys completed by 1,753 end-users at five of these six sites. In the studyâs first round, internal government factors shaping the implementation of community municipal portals, as well as usage patterns and end-user demographics, are identified. The studyâs second and third rounds use these results to test a new theoretical framework that comprises both internal government factors and individual perceptions. Importantly, information quality is suggested to be a key individual perceptions factor that not only affects successful community municipal portal diffusion, but also plays a pivotal role in mediating the effect of internal government factors on a personâs use of a community municipal portal site.
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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 | 0.003 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.002 |
| Open science | 0.000 | 0.000 |
| 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".