doi:10.1017/S0003055410000134 Coevolution of Capitalism and Political Representation: The Choice of Electoral Systems
Bibliographic record
Abstract
Protocorporatist West European countries in which economic interests were collectively organizedadopted PR in the first quarter of the twentieth century, whereas liberal countries in which eco-nomic interests were not collectively organized did not. Political parties, asMarcus Kreuzer points out, choose electoral systems. So how do economic interests translate into party political incentives to adopt electoral reform? We argue that parties in protocorporatist countries were “representative ” of and closely linked to economic interests. As electoral competition in single member districts increased sharply up to World War I, great difficulties resulted for the representative parties whose leaders were seen as interest committed. They could not credibly compete for votes outside their interest without leadership changes or reductions in interest influence. Proportional representation offered an obvious solution, allowing parties to target their own voters and their organized interest to continue effective influence in the legislature. In each respect, the opposite was true of liberal countries. Data on party preferences strongly confirm this model. (Kreuzer’s historical criticisms are largely incorrect, as shown in detail in the online supplementary Appendix.) Marcus Kreuzer’s commentary on our article oneconomic interests and the origins of elec-toral systems (Cusack, Iversen, and Soskice 2007; hereinafter CIS) raises an important set of is-sues about the role of politics, to which this article is largely addressed. (He also questions the accuracy of our historical work in constructing a coordina-tion index, arguing that 12 key assessments we make are incorrect. He is almost completely wrong: 11 of his 12 “corrections ” lack historical basis. Indeed, he provides scant evidence using multiple incorrect cita-tions and based in part on misunderstandings of our categories.1 We set out, at considerable length, de-tailed historical evidence in support of our assessments in the online supplementary Appendix, Section 1, which we hope the reader will consult, at
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.002 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.003 | 0.004 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.006 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.008 | 0.003 |
| Insufficient payload (model declined to judge) | 0.972 | 0.960 |
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".