Bibliographic record
Abstract
This chapter provides an overview of the way liberal parties have been studied in the literature. It discusses the applicability of the concept of party family to liberal parties before presenting the main findings in the literature regarding their electoral performance, electoral sociology, participation in power, internal party organisation and the main challenges they encounter. The chapter highlights two pitfalls that persist in the literature. First, it points to the difficulties scholars face in precisely defining the contours of the liberal family, given the varieties of labels, strategic transnational affiliations, and heterogeneity in their origins and ideological traditions. Common features among liberal parties appear to be more related to what they do , such as the way they exercise power, rather than to what they are . Second, the chapter identifies a significant geographical imbalance in the study of liberal parties. While the Canadian and Western European liberal parties have been extensively studied in both comparative terms and single case studies, liberal parties evolving in other geographical contexts have mostly been studied in research on transition and democratisation rather than as members of the liberal party family. In this context, we outline how further comparative research can enhance the way in which scholars understand this party family.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.004 | 0.003 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.062 | 0.011 |
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".