The Office of Premier of Ontario 1945-2010: Who Really Advises?
Bibliographic record
Abstract
This article focuses on the composition of the Ontario Premier�s office and uses an institutionalist approach to put the influence of advisors in context. It looks at expenditures attributed in the Public Accounts to the Premier�s Office and staffing. It assumes that the number of advisors and their placement in the decision-making hierarchy should have a material impact on the quantity and quality of the advice being received by the Premier. Among other things the articles shows that the classic policy/administration divide was not clearly defined in Ontario. Instead it exhibits a back-and-forth habit of experimentation that depended on the personality of the prime minister, the capacities of political and bureaucratic advisors, and the stages of the governmental cycle. There have been discernible cycles in the hiring of political staff and in the growth of expenditures that would indicate the Premier�s Office was more concerned with campaign preparations and externalities than it was in rivaling bureaucratic influence. Compared to Ottawa, where the structures of the Prime Minister�s Office and the Privy Council Office have been far more distinct in this similar time frame, the Ontario experience reveals itself as one of constant experimentation.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.003 | 0.010 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.008 |
| Science and technology studies | 0.006 | 0.004 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".