Paper prepared for presentation at the 2007 Annual Meetings of the Canadian Political Science Association
Bibliographic record
Abstract
Since 2003, the audience participation television series Canadian Idol has featured young karaoke singers from across Canada being removed one-by-one from competition based on viewer televoting each week. The hugely popular show is one of many local versions based on a franchise that began in the UK as Pop Idol and achieved success in the USA as American Idol. The franchise has attracted such an enthusiastic following that voting outcomes are often treated as hard news in local media outlets. Viewers span a range of age cohorts and those who vote for an Idol contestant may not cast a ballot for a political candidate. This idiosyncrasy is a prime research opportunity, given that federal election turnout has been declining and alarmingly low among youth in particular. This discussion paper provides the basis for primary research into what political scientists can learn from Canadian Idol. Ultimately, it provides a foundation for answering the question: do reality TV voters also vote in general elections?
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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 | 0.002 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.001 |
| Scholarly communication | 0.005 | 0.001 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.506 | 0.100 |
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; the direct Gemma label and the distilled Codex classifier agree on what is shown here.
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".