Determining tax rates: Are property tax rates determined on the basis of political factors, by politicians?
Bibliographic record
Abstract
The author has granted a non exclu siv e lic en ce allow ing the N ational Library o f Canada to reproduce, loan, distribute or sell cop ies o f this th esis in microform, paper or electron ic formats.The author retains ownership o f the c o p y r i^t in this th esis.N either the th esis nor substantial extracts from it may be printed or otherwise reproduced w ithout the author's perm ission.L'auteur a accordé une licen ce non ex clu siv e permettant à la Bibhothèque nationale du Canada de reproduire, prêter, distribuer ou vendre des co p ies de cette th èse sous la forme de m icrofiche/film , de reproduction sur papier ou sur format électronique.L 'auteur conserve la propriété du droit d'auteur qui p rotège cette thèse.N i la thèse ni d es extraits substantiels de c e lle -c i ne doivent être imprimés ou autrement reproduits sans son autorisation.
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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 | 0.007 | 0.053 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".