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Record W1519144303

The “Continuous Collaborators” in Italy. Hybrids between Employment and Self-employment.

2006· preprint· en· W1519144303 on OpenAlexaboutno aff
Ulrike Mühlberger, Silvia Pasqua

Bibliographic record

VenueRePEc: Research Papers in Economics · 2006
Typepreprint
Languageen
FieldSocial Sciences
TopicDigital Economy and Work Transformation
Canadian institutionsnot available
Fundersnot available
KeywordsQuarter (Canadian coin)Work (physics)Labour economicsSocial securityBusinessSelf-employmentLabour lawTemporary workDuration (music)Demographic economicsEconomicsMarket economyFinanceEntrepreneurshipEngineeringGeography
DOInot available

Abstract

fetched live from OpenAlex

Over the last decade Italy has seen a strong increase in the number of workers on the border between self-employment and employment. Depending on the data source the “parasubordinati”, i.e. workers with a “contract of continuous collaboration” (collaborators) represented between 1.8% (ISTAT, 2004) and 5.3% (Alteri and Oteri , 2004) of the Italian labour force. Since most of them work only for one company and are, moreover, strongly integrated into the firm of the contract partner, we argue that the Italian labour and social security law strongly discriminates against these workers who are, in fact, very close to employees. We investigate whether and in what respect the group of the collaborators differs from the group of employees and the group of the self-employed using the Italian Labour Force Survey (ILFS) of 2004 (4th quarter). Additionally, we analyse the short-term labour market transitions of collaborators to other labour market statuses. In contrast to other European countries, these collaborators are not low qualified workers, but young, highly educated professionals. At the same time the contracts of continuous collaboration are not a port of entry into the labour market nor do we find that these contracts are a vehicle to more stable jobs. However, they seem to be a possibility for women to work part-time.

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)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.891
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0010.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.019
GPT teacher head0.306
Teacher spread0.287 · 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 teacher head, not a consensus.

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

Citations10
Published2006
Admission routes1
Has abstractyes

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