Leave it to the Amateurs: A Career Development Explanation of Political Inexperience among Members of the Canadian Parliament
Bibliographic record
Abstract
In many advanced democracies, political scientists have lamented the rise of professional politicians as a challenge to the effective representation of diverse electorates. In contrast, their relative absence from Canadian federal politics gives rise to concerns over high levels of political amateurism among Canadian MPs. This study, thus, seeks to account for the numerical weakness of individuals with an occupational background in politics in the Canadian Parliament. It utilizes both individual-level quantitative data on MPs serving between the 35th and 41st Parliaments, inclusive, as well as material from qualitative interviews with over seventy former MPs. Conceptualizing the field of politics as a career in itself, and drawing on career development theory, the study finds that at the key stages of establishing, maintaining, and disengaging from a federal political career, there are specific challenges that are not significantly ameliorated by the possession of professional experience in politics itself. Professional politicians, therefore, have no major advantage over those with non-political occupational backgrounds in their career development. Furthermore, by acknowledging the existence of different types of professional politician, it finds that those whose primary occupational background was in politics itself to be in a distinct minority, but the extent of political amateurism is challenged by a much larger minority of MPs whose primary occupation was non-political but who still possess some secondary or electoral experience prior to entering Parliament.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.028 | 0.010 |
| Scholarly communication | 0.006 | 0.002 |
| Open science | 0.002 | 0.005 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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".