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Record W2136227760 · doi:10.1017/s000305540282024x

The Search for Good Government: Understanding the Paradox of Italian Democracy. By Filippo Sabetti. Montreal: McGill–Queens University Press, 2000. 288p. $34.95.

2002· article· en· W2136227760 on OpenAlexaboutno aff
Franklin Hugh Adler

Bibliographic record

VenueAmerican Political Science Review · 2002
Typearticle
Languageen
FieldSocial Sciences
TopicPolitical Economy and Marxism
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsProsperityDemocracyPolitical scienceState (computer science)InstitutionSociologyPolitical economySocial scienceLaw

Abstract

fetched live from OpenAlex

Filippo Sabetti has written an important book, not just for specialists in Italian politics, but also for those more generally interested in comparative politics. Poor government performance has often been associated with the Italian state, so much so that foreign scholars often used Italy as an ideal locale to probe the seminal causes of political pathology. Edward Banfield's (1958) The Moral Basis of a Backward Society , for example, attributed poor political performance to the particular beliefs and attitudes of Italians, to an inadequate moral basis he identified as “amoral familism.” The village Banfield studied, Chiaromonte (which he called Montegrano), soon became a model for “backward societies” in the comparative literature and later was woven into game theoretic concerns, such as the tragedy of the commons and the prisoner's dilemma. Banfield's “culturalist” approach was later refined in Robert Putnam's (1993) Making Democracy Work . Rather than condemning all Italy to pathological status, as Banfield's Montegrano writ large, Putnam compared the “unsuccessful” South with the civic-minded North, where a density of associations and an abundance of “social capital” not only made “democracy work,” but also contributed to economic prosperity. Putnam later extended this analysis of associability and social capital to the United States, most famously in his work on “bowling alone.”

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 distilled prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.

metaresearch head score (Codex)0.002
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesScience and technology studies
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.968
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.011
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.045
GPT teacher head0.301
Teacher spread0.256 · 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; both teacher heads agree on what is shown here.

Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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
Published2002
Admission routes1
Has abstractyes

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