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Record W2908113782 · doi:10.5281/zenodo.2532879

Bilancio Pop della Città di Torino - Popular Financial Reporting City of Turin 2016/2017

2018· article· en· W2908113782 on OpenAlexaboutno aff
Paolo Biancone, Silvana Secinaro, Valerio Brescia

Bibliographic record

VenueZenodo (CERN European Organization for Nuclear Research) · 2018
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicDiverse academic and cultural studies
Canadian institutionsnot available
Fundersnot available
KeywordsBusinessPolitical scienceHumanitiesGeographyArt

Abstract

fetched live from OpenAlex

Citizens are increasingly demanding public responsibility and government programs that are more attentive to the real needs of the territory, particularly in terms of managing public resources. In English-speaking countries, a form of social reporting is widespread, which has characteristics of transparency and understanding even for those who do not normally deal with the economic assessment and the services provided. This reporting is called Popular Financial Reporting, renamed the Pop Budget. The City, which has always been innovative in terms of reporting and related communication, has already experimented with the support of the University of Turin in drafting the 2014/2015 POP budget. The document was produced following the best practices that are present internationally in the English-speaking countries. The Pop budget is indeed a widespread document in the United States, Canada and Australia. The Department of Management of the University of Turin has produced the document according to guidelines and processes defined by the Scientific Steering Committee that has taken care of the methodological references and operational supervision together with the working group of methodological and operational application that has busy making the document.

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)0.001
metaresearch head score (Gemma)0.002
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.388
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0010.001
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.005

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 head0.110
GPT teacher head0.254
Teacher spread0.144 · 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 designNot applicable
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
Published2018
Admission routes1
Has abstractyes

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