Public Policy and the Moment of Crisis in New Brunswick: An Interview with Donald Savoie
Bibliographic record
Abstract
Universite de Moncton professor Donald Savoie is well known to New Brunswickers. He has been a voice for fiscal responsibility, and he has made a career of thinking outside the confines of our much-cherished programs of distributive federalism—programs that have favoured central Canada at the expense of the regions. This interview with Professor Savoie picks up from an essay he wrote in the first issue of the Journal of New Brunswick Studies/Revue d’etudes sur le Nouveau-Brunswick . That essay urged New Brunswickers to make the most of the fiscal crisis we are now in, calling on us to act decisively to get our fiscal house in order before calamity (in the form of economic collapse) does it for us. Because of the interest in Professor Savoie’s essay and the importance of his message in a province searching for alternatives to deficit spending and increasingly tight-fisted federalism, we thought it wise to continue the discussion. Resume Bien connu des Neo-Brunswickoises et des Neo-Brunswickois, Donald Savoie est professeur a l’Universite de Moncton. Il s’est fait le defenseur de la responsabilite financiere et, depuis le debut de sa carriere, ne cesse pas de penser au-dela des formules consacrees de nos programmes de federalisme distributif – programmes qui ont favorise le centre du Canada aux depens des regions. La presente entrevue avec M. Savoie se veut la suite de l'article qu'il a contribue au premier numero de la Revue d’etudes sur le Nouveau-Brunswick . Dans ce premier article, il encourage les gens du Nouveau-Brunswick a tirer parti de la crise financiere dans laquelle ils se trouvent a l’heure actuelle et d’agir de maniere resolue afin d’assainir les depenses publiques avant que calamite (sous la forme d’effondrement economique) s’en occupe. Compte tenu de l’interet qu’a suscite l’article precedant de M. Savoie et de l’importance de son message dans une province qui est a la recherche de solutions de rechange afin de mettre fin au deficit actif et du federalisme de plus en plus avare, nous avons cru bon de poursuivre la discussion.
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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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.033 | 0.015 |
| Scholarly communication | 0.013 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.016 |
| Insufficient payload (model declined to judge) | 0.005 | 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 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".