Political Parties Abroad. A New Arena for Electoral Politics
Bibliographic record
Abstract
This Special Issue contributes to the growing literature on parties abroad. Expansive citizenship has transformed and reinforced the civic and political links between emigrants and their home country. Political parties face the dilemma of engaging or not in this new arena for electoral politics and must consider how. However, until recently the literature on transnationalism and on party politics has surprisingly largely overlooked this issue. This introduction identifies the existing gaps in the literature, and stresses two main questions that remains largely unanswered, namely (1) why and how parties decide to campaign abroad, and (2) how voters abroad are receptive to these campaigns and operate their party choice in this specific context. The five articles offer a mix of case studies and comparative perspective, and quantitative and qualitative analyses. This case selection allows to explore the diversity of strategies adopted by political parties abroad in different settings, with different tools. The results illustrate the impact of local party branches and entrepreneurs’ outreach and local campaigns on mobilisation, turnout, and the result of elections, but also show that emigrants’ vote choice is influenced both by the context of their country of origin and of their country of residence.
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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 | 0.001 |
| Science and technology studies | 0.003 | 0.003 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.000 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.016 | 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".