Bibliographic record
Abstract
The paper develops a formal theoretical model of expenditures for a typical Canadian provincial government. The model is kept simple but useful by restricting the endogenous variables to four important budgetary categories: highway spending, hospital care expenditures, spending on schools and universities, and "all other" spending. Tax rates are also endogenous to the system. The choice of these four expenditure categories is linked to the original motivation for the model, which was to assist in explaining provincial construction spending. The theory has three elements: first, a utility function, which depends positively on the amounts provided of government services of various kinds, as well as on the income left to the public after taxes and borrowing; second, a budget constraint linking expenditures and revenues; and finally, a set of equations which show how much spending is required in order to provide the quantities of services entering as arguments into the utility function. The reduced form model developed from the theory is then fitted to expenditures data for each of the ten provinces over the 1952-1970 period. Fits are generally good. Tax equations, though not presented here, also fitted well. Provincial income levels, beginning year stocks of structures, rates of matching grants, construction prices and the closeness of elections are the main exogenous variables that prove important in explaining per capita expenditures within each of the four budgetary categories.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.003 | 0.001 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.025 | 0.002 |
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".