Why Can't We Be Friends? Informal Relations, Public Policy, and Federalism in Canada
Bibliographic record
Abstract
Canada is an "under-institutionalized" federation (Cameron and Simeon, 2002b).In the extensive world of intergovernmental relations (IGR) which exist between the federal, provincial and territorial governments, formal relations are said to be "the tip of the iceberg" (Kernaghan, 1985: 156).This leaves a good deal of governmental activity in Canada within the realm of 'informal relations,' a world of intergovernmental relations between public servants without formal rules to guide the process.Broadly considered, those relations are important (Inwood et al., 2011).However, scholarship is not neutral on this point: informal relations are frequently treated as being unstructured and inefficient (Meekison et al., 2004).This dissertation tackles the issue of informal relations by asking, at the level of public servants, what are the effects of informal relations on intergovernmental relations?If they are 'important,' what is the nature of this importance?Using a model derived from primary research, the study explores how context shapes informal relations in three case studies of intergovernmental relations: the Agreement on Internal Trade, the Health Care Innovation Working Group, and the Ministerial Conference on the Canadian Francophonie.By focusing on variables at various levels, one can better understand how informality operates in a given context.The study makes two central arguments: first, that informality should not be equated with disorder.By examining the environment in which informal relations occur, one can better understand the effects of those relations.Second, while informal relations are important, this importance must also be understood in context: informal relations have effects on the speed and efficiency of work among public servants, but the environment in which they occur plays an important role in limiting the effects of informality.Thus, the effects of informal relations are shaped by context.Informal relations are present and 'important,' but although they are 'informal,' they are still structured by the environment of Canadian federalism.This project would not have gone far without the willingness of public servants throughout Canada to take time out of their busy schedule to talk to me.Nearly 50 individuals did, and were genuinely interested in the study and in sharing their experiences.Confidentiality (and space) prevent me from thanking them all individually, but if I can use one public servant as a proxy, I am particularly indebted to Chantal Alarie with the Ministerial Conference on the Canadian Francophonie.Chantal championed my research, allowed me to have access to teleconferences and prodded her colleagues to make time in their schedules (as well as agreeing to be thanked by name).Merci Chantal.My principal advisors, Dr. Jonathan Malloy and Dr. Raffaele Iacovino, were consistently available, encouraging, and accepting of my particular path through the PhD.When I told them in 2014 that I intended to write the bulk of my dissertation from my home town of Winnipeg, they expressed no concern (at least not openly!)even though it must have seemed like I was asking for enough rope to hang myself with.Having thus far avoided the noose, I thank them profoundly for their faith and understanding.
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.035 | 0.019 |
| Scholarly communication | 0.011 | 0.003 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| 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".