Bigger <i>Is</i> Better: Reducing the Cost of Local Administration by Increasing Jurisdiction Size in Ontario, Canada, 1995–2010
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In recent decades, the belief that larger municipalities can better capture economies of scale led to compulsory amalgamations in several countries. This article examines such a program of compulsory amalgamations in Ontario, Canada, during the late 1990s and early 2000s. By exogenously deciding on a course of municipal restructuring, and leaving a large comparison group of nonamalgamated municipalities within the same institutional framework, the Ontario reforms created a quasi-experiment on the importance of scale for local government. Using a difference-in-differences methodological approach, this article exploits the quasi-experimental setting of the Ontario reforms to examine the causal effect of jurisdiction size on the cost of local administration. The main empirical finding in this article is that increasing local jurisdiction size reduces the cost of local administration. The results provide the most convincing evidence to date that economies of scale exist in local administration and can be captured through consolidation.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it