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
This article uses a new dataset of nearly 2,000 municipal elections from 1874 to 2018 to estimate the size of municipal incumbency advantage in Canada for the first time. Incumbency increases the probability that a candidate will win the next election by more than 30 percentage points and accounts for well over half of overall incumbent success. Incumbency advantage varies modestly by institutional context but varies substantially over time, with a distinct decrease during a period of partisan elections in the mid-twentieth century. These findings represent one of the first estimates of municipal incumbency advantage in an advanced democracy outside the United States and provide a new approach to estimating and comparing incumbency advantage in multi-member and single-member districts. The findings suggest important similarities between Canadian and American municipal elections, demonstrate that incumbency advantage has varied significantly at the municipal level over time, and illustrate the value of historical election data for scholars of urban electoral politics.
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