The Impact of Representation Per Capita on the Distribution of Federal Spending and Income Taxes
Bibliographic record
Abstract
Abstract. A vote-maximizing incumbent government is expected to adjust discretionary spending and taxation in ways that increase its probability for re-election. Unequal voters per electoral district in Canada distort this calculation in favour of small electoral districts. Using two measures of federal expenditures, and one of income taxes, between the years 1961–2000, empirical estimates indicate that greater representation per capita (lower relative electoral district populations) results in higher federal spending, and lower income taxes, per capita, even after controlling for income and unemployment. Résumé. Un gouvernement en place tentant de maximiser les votes en sa faveur est censé ajuster les dépenses discrétionnaires et les impôts de manière à augmenter la probabilité de sa réélection. L'inégalité du nombre d'électeurs des districts électoraux au Canada crée une distorsion en faveur des districts de petite taille. En utilisant deux mesures des dépenses fédérales et une mesure des impôts sur le revenu entre 1961 et 2000, nos résultats empiriques montrent qu'une plus forte représentation par habitant (plus petits districts électoraux) entraîne des dépenses fédérales plus importantes et des impôts sur le revenu moins élevés par personne, même en contrôlant pour le revenu et le taux de chômage.
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 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 | 0.002 | 0.002 |
| 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 | 0.004 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".