The inflated measures of governmental instability (LIEPP Working Paper, n°96)
Bibliographic record
Abstract
Most analyzes of government instability in parliamentary democracies rests on a standard definition of what counts as a new government. Three criteria are used. A new government exists whenever there is a new Prime Minister, after the occurrence of a general election, and whenever the partisan composition of the government changes. Obviously fruitful in many respects, the definition is problematic if we are interested in the political phenomenon of government stability and instability; governmental durability based on the standard definition of governments is not a valid and useful measure of stability in many parliamentary systems. We argue that this measure from one perspective is too inclusive (not any change in government's partisan composition signifies instability), and from another angle too narrow (focusing almost exclusively on a government as a whole.) We investigate how changes in conceptualization of what constitute new governments, affects the degree of instability in parliamentary democracies. Clearly, definitions make a difference and we demonstrate that countries might be characterized as unstable from one perspective, yet stable from another. Clearly, the commonly used definition of government used to measure government duration inflates instability, at least for some countries. We demonstrate that using more precise definitions of government longevity - ones that do not equate any changes in government's partisan composition as a sign of instability - yield important ramifications for the rank-order of countries' governments instability.
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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 | 0.011 | 0.041 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.011 | 0.024 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.016 | 0.003 |
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".