Election Pledges and their Enactment in Coalition Governments: A Comparative Analysis of Ireland
Bibliographic record
Abstract
This study examines election pledges and their enactment in Ireland. Much previous research focused on countries where single‐party governments are the norm (the United Kingdom, Canada and Greece), and the presidential system of the United States with separation of powers. The present research draws on evidence from existing studies of pledge enactment in Ireland and the Netherlands. In addition, it adds new evidence on election pledges and their enactment in the most recent Irish government: the majority centre‐right coalition of Fianna Fáil and the Progressive Democrats, 2002–2007. By adding this new evidence, we are able to make stronger inferences on the impact of coalition governance on the types of pledges made and rates of pledge enactment. We also study the impact of prominent mechanisms of coalition governance – government agreements and ministerial portfolio allocations – on the likelihood of pledge enactment. In addition, in an effort to move beyond existing research, we present evidence on the extent to which election pledges are featured in media reports during the election campaign.
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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 | 0.010 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.005 | 0.006 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".