Revisiting Local Campaign Effects: An Experiment Involving Literature Mail Drops in the 2007 Ontario Election
Bibliographic record
Abstract
Abstract.An invariant feature of constituency election campaigns is the literature mail drop, usually a one-page leaflet or card left at the door profiling the candidate and appealing for electoral support. In this article, we report on a field experiment designed to assess the effects of such mail drops. The experiment was conducted during the 2007 Ontario provincial election campaign in the constituency of Cambridge and entailed distributing literature for the Green party candidate in that constituency. After randomly assigning constituency polls to treatment and control groups, and delivering the Green candidate's partisan literature only to the selected treatment group polls, we compared the candidate's support levels in the treated polls with those in the control group. Our research detected a modest effect associated with the literature drop. The effect was largely limited to constituency neighbourhoods fitting at least part of the Green party's traditional demographic, that is, those with higher than average socio-economic status. Résumé.Un trait commun des campagnes électorales au niveau des circonscriptions est la distribution de publipostages. Il s'agit habituellement d'un dépliant d'une page déposé dans la boîte aux lettres et donnant le profil du candidat tout en invitant les gens à voter pour lui. Notre article porte sur une expérience que nous avons menée pour évaluer les effets de ces publipostages sur le vote. Au cours de la campagne des élections provinciales de l'Ontario, en 2007, dans la circonscription de Cambridge. nous avons distribué des documents sur le candidat du Parti vert de cette circonscription. Les bureaux de scrutin ont étés divisés, au hasard, en deux groupes, soit un groupe de traitement et un groupe de contrôle. Nous avons distribué les documents seulement aux électeurs du premier groupe. Après l'élection, nous avons comparé les niveaux d'appui au candidat vert dans les deux groupes. Les résultats montrent un effet modeste associé à la distribution des publipostages. L'effet observé était en grande partie limité aux quartiers répondant, en partie du moins, au profil démographique traditionnellement favorable aux partis écologiques, soit les quartiers ayant un statut socio-économique plus élevé que la moyenne.
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 | 0.003 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.007 | 0.001 |
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".