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Record W6958665976 · doi:10.7384/107275

Interventi e misure di contrasto alla poverta lavorativa in Italia

2022· article· it· W6958665976 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

aboutThe title or abstract carries a Canadian signal from the geographic lexicon.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueInstitutional Research Information System (Università degli Studi di Trento) · 2022
Typearticle
Languageit
FieldBusiness, Management and Accounting
TopicLegal and Labor Studies
Canadian institutionsnot available
Fundersnot available
KeywordsPovertyRedistribution (election)Work (physics)WagePublic policyQuarter (Canadian coin)Minimum wage

Abstract

fetched live from OpenAlex

A quarter of Italian workers have a low individual wage (i.e. below 60% of the median), and more than one in 10 are in poverty (i.e. they live in a household with a net equivalent income below 60% of the median). In the public debate, in-work poverty is often linked to low wages whereas it is the result of a process that goes far beyond wages, and concerns also work intensity, the household structure, and redistribution policies. A strategy against in-work poverty therefore requires multiple instruments to support workers’ wages, increase the number of earners, and ensure an effective redistributive system. In this contribution, after a discussion of the mechanisms that lead to in-work poverty, we discuss four policy packages to address in-work poverty in Italy.

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.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Insufficient 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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.807
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0020.004
Science and technology studies0.0040.000
Scholarly communication0.0010.008
Open science0.0010.003
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.056
GPT teacher head0.288
Teacher spread0.232 · 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