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Record W7038984145

La tutela dei minori nell’eta del consenso digitale. Un approccio gius-cibernetico

2019· article· it· W7038984145 on OpenAlexaboutno aff

Bibliographic record

VenueInstitutional Research Information System University of Ferrara (University of Ferrara) · 2019
Typearticle
Languageit
FieldEngineering
TopicProsthetics and Rehabilitation Robotics
Canadian institutionsnot available
Fundersnot available
KeywordsPower (physics)Quarter (Canadian coin)Work (physics)
DOInot available

Abstract

fetched live from OpenAlex

L’autore fa un’analisi del mondo digitale mostrando come risulti difficile individuare un corretto inquadramento della natura giuridica del cyberspazio. Dal punto di vista giuridico, Internet non è un soggetto; la realizzazione dei vari rapporti telematici in Rete richiama l’immagine di un luogo dove si instaurano relazioni commerciali, personali o in cui vengono commessi atti illeciti. In che misura effettivamente il diritto regoli il comportamento nel cyberspazio è una questione a sé. Il cyberspazio è uno spazio distinto e diverso dallo spazio reale, in cui le ormai delegittimate autorità pubbliche dei luoghi reali sono sostituite dagli utenti della Rete, che dettano per se stessi regole atte a realizzare i loro desideri e bisogni. L’assenza di frontiere fisiche nel cyberspazio determina il venir meno della territorialità, carattere intrinseco di un ordinamento giuridico, sicché appare impossibile delimitare l’ambito di operatività delle norme statali, nel cyberspazio. L’autore rivolge poi uno sguardo particolare all’approccio dei minori ad internet e conclude osservando che finché il legislatore continuerà ad immaginare una perfetta simmetria tra azioni offline e azioni online, nessuna normazione preventiva risulterà efficace: il confine tra offline e online potrà risultare netto solo agendo sulle scelte di design degli spazi virtuali su Internet.

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)0.007
metaresearch head score (Gemma)0.017
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.048
Threshold uncertainty score0.161

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0070.017
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0030.004
Science and technology studies0.0040.008
Scholarly communication0.0190.019
Open science0.0020.007
Research integrity0.0050.007
Insufficient payload (model declined to judge)0.0480.008

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 head0.028
GPT teacher head0.223
Teacher spread0.195 · 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 designTheoretical or conceptual
Domainnot available
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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