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Record W6889464535 · doi:10.25647/liepp.wp.096

The inflated measures of governmental instability (LIEPP Working Paper, n°96)

2022· other· en· W6889464535 on OpenAlexaboutno aff

Bibliographic record

VenueDirection des ressources et de l'information scientifique · 2022
Typeother
Languageen
Field
Topic
Canadian institutionsnot available
FundersAgence Nationale de la Recherche
KeywordsGovernment (linguistics)ConceptualizationPhenomenonSign (mathematics)PoliticsMeasure (data warehouse)Stability (learning theory)Quarter (Canadian coin)

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.011
metaresearch head score (Gemma)0.041
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.016
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0110.041
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0110.024
Science and technology studies0.0020.005
Scholarly communication0.0070.006
Open science0.0010.004
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0160.003

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.

Opus teacher head0.028
GPT teacher head0.265
Teacher spread0.237 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreOther

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".

Quick stats

Citations0
Published2022
Admission routes1
Has abstractyes

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