Enterprise Application Integration; Healthcare Organizations; Information Technology ; Large Organizations; Local Government Authorities
Bibliographic record
Abstract
This chapter will compare the emergence of e-government in Denmark and Canada with a particular emphasis on the municipal and inter-governmental dimensions to the digital adaptation of the public sector. Denmark and Canada share many general traits in terms of the emergence of e-government in both countries. Internet and telecommunications infrastructures are well developed, widely accessible, and (on a relative basis) affordably priced; both countries enjoy high standards of living. Local governments differ greatly, however, in terms of political responsibility and autonomy, financing capacities, and degrees of influence over more senior order government levels. These differences are particularly evident in the field of healthcare, but they are also more generalized and the implications for e-government will be considered in terms of likely future trajectories of public sector reform and democratic legitimacy in each country. In particular, an important lesson derived from this chapter is that Canada faces greater challenges than Denmark in collaborating across jurisdictional boundaries and that weaker municipal capacity within the Canadian context is central to this concern.
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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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.006 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.015 | 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".