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Record W3196361322 · doi:10.3390/jrfm14090435

Political Participation in the Risk Society: The Italian Case

2021· article· en· W3196361322 on OpenAlexvenueno aff
Marianna Bartiromo, Enrico Ivaldi

Bibliographic record

VenueJournal of risk and financial management · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Capital and Networks
Canadian institutionsnot available
Fundersnot available
KeywordsPoliticsWork (physics)Risk societySet (abstract data type)Political scienceSociologySocial scienceLaw

Abstract

fetched live from OpenAlex

The risk society has profoundly changed our way of life. Among the social phenomena most affected by its effects is undoubtedly political participation and the degree of trust in institutions. This work aims, through the construction of two different indices, to answer the question “How does the risk society influence conventional participation and trust in institutions?”. The Indagine Multiscopo sulle famiglie and the Benessere Equo Sostenibile surveys provide a complete set of indicators to assess specific aspects of Italian daily life and well-being. This work uses a series of data from these surveys to analyze political participation and trust in institutions in Italy in 2019 at regional level using two composite indices obtained through the application of the MPI method. The result of this paper shows no particular effects of the risk society on conventional forms of political participation. Instead, the effects of the risk society are fully visible on levels of trust in institutions.

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)0.002
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.030
Threshold uncertainty score0.060

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.002
Science and technology studies0.0020.003
Scholarly communication0.0030.001
Open science0.0000.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.016
GPT teacher head0.296
Teacher spread0.280 · 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 designObservational
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

Citations1
Published2021
Admission routes1
Has abstractyes

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