Determinants of web site information by Spanish city councils
Bibliographic record
Abstract
Purpose The purpose of this research is to analyse the web sites of large Spanish city councils with the objective of assessing the extent of information disseminated on the internet and determining what factors are affecting the observed levels of information disclosure. Design/methodology/approach The study takes as its reference point the existing literature on the examination of the quality of web sites, in particular the provisions of the Web Quality Model (WQM) and the importance of content as a key variable in determining web site quality. In order to quantify the information on city council web sites, a Disclosure Index has been designed which takes into account the content, navigability and presentation of the web sites. In order to contrast which variables determine the information provided on the web sites, our investigation bases itself on the studies about voluntary disclosure in the public sector, and six lineal regressions models have been performed. Findings The empirical evidence obtained reveals low disclosure levels among Spanish city council web sites. In spite of this, almost 50 per cent of the city councils have reached the “approved” level and of these, around a quarter obtained good marks. Our results show that disclosure levels depend on political competition, public media visibility and the access to technology and educational levels of the citizens. Practical implications The strategy of communication on the internet by local Spanish authorities is limited in general to an ornamental web presence but one that does not respond efficiently to the requirements of the digital society. During the coming years, local Spanish politicians will have to strive to take advantage of the opportunities that the internet offers to increase both the relational and informational capacity of municipal web sites as well as the digital information transparency of their public management. Originality/value The internet is a potent channel of communication that is modifying the way in which people access and relate to information and each other. The public sector is not unaware of these changes and is incorporating itself gradually into the new network society. This study systematises the analysis of local administration web sites, showing the lack of digital transparency, and orients politicians in the direction to follow in order to introduce improvements in their electronic relationships with the public.
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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 | 0.002 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".