Bibliographic record
Abstract
Federal property issues - especially those involving divestiture - create political disputes at all levels of government. Federal Property Policy in Canadian Municipalities analyzes the emergence of many of these issues involving military bases, airports, and other facilities in communities across Canada. With careful analysis the contributors show the underlying patterns and causes of these conflicts and their resolutions while emphasizing intergovernmental relations and the social forces that are active in property issues. Contributors examine general federal policy as well as issues pertinent to British Columbia, the Toronto waterfront, New Brunswick, and Newfoundland and Labrador. The unprecedented number of cases discussed in these essays provides general conclusions and recommendations for a new orientation that will take local interests and preferences into account from the outset of decision-making. Public property is an understudied field of public policy, particularly as it concerns municipal government. Federal Property Policy in Canadian Municipalities presents a comprehensive treatment of federal property, changes in policy, and the effects these changes have on various levels of government. Contributors include Jeff Braun-Jackson (Memorial University of Newfoundland), Pierre Filion (University of Waterloo), Michael C. Ircha (University of New Brunswick), Leonard Wade Locke (Memorial University of Newfoundland), Robert MacKinnon (University of New Brunswick in Saint John), Kurt Peacock (University of New Brunswick in Saint John), Christopher Sanderson (Government of Manitoba), Tracy Summerville (University of Northern British Columbia), Stephen Tomblin (Memorial University of Newfoundland), Gary N. Wilson (University of Northern British Columbia), John Young (University of Northern British Columbia), and Robert A. Young (University of Western Ontario).
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 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.010 |
| Science and technology studies | 0.037 | 0.006 |
| Scholarly communication | 0.011 | 0.002 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.009 | 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".