Bibliographic record
Abstract
The Comparative Manifestos Project (CMP) was born out of the activities of the original Manifesto Research Group (MRG). This group is not to be confused with the more recently formed MRG, the ECPR Standing Group on Party Manifestos, concerned with the computerised analysis of political texts, founded by Paul Pennings of the Vrije University in Amsterdam a couple of years back. The first MRG began its activities under the aegis of the ECPR at the Florence Joint Sessions in 1980, and continued throughout the 1980s to collect, code, and analyse party manifestos (election programmes) for nineteen countries from 1945 to 1983. The democracies covered were mainly in Europe but also included the USA, Canada, Australia, New Zealand, Israel, Sri Lanka and Japan. The basic idea at first was to see what cleavages divided the parties, how many cleavages there were, and whether parties had converged or diverged along them during the post-war period.
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 | 0.094 | 0.116 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.014 | 0.027 |
| Science and technology studies | 0.008 | 0.032 |
| Scholarly communication | 0.019 | 0.033 |
| Open science | 0.003 | 0.012 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.010 | 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".