Why Do Per-Household Expenditures Differ between Municipalities?
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
The purpose of this paper is to identify the factors that account for variation in per-household expenditures between municipalities. Using multiple regression techniques, we find that it is advantageous for a community to have growth and a high percent of non-residential to residential assessment. We also find that larger sized municipalities have higher per-household expenditures. However, the impact of size on the various categories is mixed with some being subject to economies of scale whereas others are subject to diseconomies. Thus, there is a potential for municipalities to lower their expenditures by growth, by increasing commercial and industrial assessment and by consolidating with other municipalities those services that are subject to economies of scale. Since 80% of expenditures in Ontario are financed by local revenues such as taxes and user fees, the determinants of expenditures should give an indication as to why these local revenue sources differ between municipalities.
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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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 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