The Institutionalisation of the Ombudsman Idea: The Case of New Brunswick's Ombudsman
Bibliographic record
Abstract
This paper is about an organisation- the office of ombudsman- and how this organisation has become an institution. Although the ombudsman concept received extensive coverage when it was first adopted in Canada during the late1960s, it has since received limited attention in public administration periodicals and textbooks. Yet, curiously, the ombudsman has quietly become a cornerstone of the administrative state in Canada, so much so that its merits are taken for granted and cited by rote, with few if any detractors to be found. As an independent officer of the legislature who is appointed to handle citizen complaints of decisions made by public servants, the office of ombudsman may be viewed as a direct form of political participation intended to ensure democratic accountability of the administrative state. But what has been the actual performance record of the office of ombudsman? That is, following its adoption, how has the office of ombudsman nestled into the democratic administrative state as a fixed institution? There is more to this research objective, however, than what might first meet the eye. Across the country at this time, there is considerable attention being devoted to the analysis of the so-called democratic deficit, or the public’s disillusionment with and
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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 | 0.011 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.036 | 0.037 |
| Scholarly communication | 0.017 | 0.008 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.006 | 0.011 |
| Insufficient payload (model declined to judge) | 0.008 | 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".