“The Machines Don’t Lie”: A Study of the Social Production of Mechanization in the Determination of Voter Intent
Bibliographic record
Abstract
Because election results are the essential measure of the popular will in liberal democracies, accurate determination of voter intent is a necessary pre-requisite since “what [N] does is not simply make a mark on a piece of paper; he [sic] is casting a vote” (Peter Winch). If every vote counts, then every valid vote must be counted – which means seeing the mark on the paper as intentional action. But, electronic voting systems are increasingly used in Canada. Given the operational vagaries of the use of such machines, the paper asks: How is voter intent mechanically achieved as a practical, social accomplishment of the human beings charged with working the machines and counting the votes?
 The paper then reports a case study of the tallying of ballots in one municipality in a recent Ontario municipal election where the official result between the two top candidates was a difference of one vote. It focuses on the social production of mechanical consistency in the determination of voter intent during the recount process.
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 | 0.005 | 0.001 |
| 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 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".