Three's a crowd in two-and-a-half-party systems : how third parties have undermined their own policy objectives in five post-war democracies
Bibliographic record
Abstract
This study examines the manners in which third parties’ electoral results and shifts in policy have affected major parties’ policy positioning. I respond to the work of Adams and Merrill (2006) and of Nagel and Wlezien (2010) by analyzing two-and-a-half-party systems that contain a centrist or a non-centrist third party. The cases include parties elected by a variety of voting systems and with various political traditions. Ultimately, I find that, over the past half-century, third parties in Austria, Canada, Germany, Ireland, and Luxembourg have regularly undermined the policy objectives most commonly associated with the these parties. A modified version of Nagel and Wlezien’s occupied-centre effect, which I call the occupied-position effect, has been present in the five examined national party systems. This finding, however, is only applicable with respect to shifts in policies that have principally been associated with third parties, what I call “key policies”, as opposed shifts in general left-right positions. The evidence presented in this study shows that the major parties in two-and-a-half-party systems have consistently responded to third-party electoral gains by becoming less supportive of third parties’ key policies. Three such policy areas are examined: welfare spending, market liberalization, and ethnonationalism. I also show that there are effects from third parties changing their own policy positions, independent of how well they do at the polls. Exacerbating the dilemma that the analyzed third parties have faced, a key-policy version of Adams and Merrill’s reverse-shift effect appears to have been present in the examined party systems. This means that the major parties have followed shifts in third parties’ policy positions by shifting their positions in the opposite directions. Thus, third parties have undermined their own policy objectives when they have expressed (and shifted to) strong key-policy positions during election campaigns. Though third parties do have a strategic option pertaining to this effect – expressing insincere, moderated policy preferences – the long-term applicability of this tactic appears limited, especially in conjunction with the problems third parties have faced regarding the occupied-position effect.
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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 | 0.003 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.012 | 0.008 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".