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Record W7001008468

I giudici di common law e la (cross)fertilization: i casi di Stati Uniti d’America, Canada, Unione Indiana e Regno Unito

2014· other· it· W7001008468 on OpenAlexaboutno aff

Bibliographic record

VenueCINECA IRIS Institutional Research Information System (University of Bari Aldo Moro) · 2014
Typeother
Languageit
Field
Topic
Canadian institutionsnot available
Fundersnot available
KeywordsVolume (thermodynamics)HastaConsumer law
DOInot available

Abstract

fetched live from OpenAlex

Il volume raccoglie le riflessioni di giovani studiosi impegnati nella realizzazione del Progetto di ricerca “IDEA Giovani Ricercatori 2011” intitolato “IurComp. Osservatorio e Portale telematico di giurisprudenza comparata: ambiti, metodi, tecniche e prassi di inte(g)razione nell’attività di Corti costituzionali, sovranazionali e internazionali” e finanziato dall’Università degli Studi di Bari “Aldo Moro” (coordinatore: dott.ssa Pamela Martino). Muovendo dal presupposto che “comunicazione” è «ogni processo consistente nello scambio di messaggi, attraverso un canale e secondo un codice, tra un sistema ... e un altro della stessa natura o di natura diver-sa» (v. Enciclopedia Treccani), il volume si propone di indagare il dialogo giurisprudenziale nell’area di com-mon law – con particolare riferimento alle esperienze costituzionali che tradizionalmente hanno animato e attualmente alimentano il dibattito intorno ai benefici derivanti dall’interscambio tra giudici oltre le frontiere nazionali, ovvero Stati Uniti d’America, Canada, Unione Indiana e Regno Unito – da una prospettiva di analisi critica che approfondisce il confronto interno alle Corti e la sua incidenza sulla propensione delle stesse alla comunicazione transnazionale e multilivello (ascendente e discendente), nel tentativo di individuare nuovi itinerari evolutivi del fenomeno.

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)0.005
metaresearch head score (Gemma)0.011
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.090
Threshold uncertainty score0.654

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0050.011
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0030.008
Science and technology studies0.0150.015
Scholarly communication0.0160.005
Open science0.0020.005
Research integrity0.0030.004
Insufficient payload (model declined to judge)0.0170.001

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 head0.037
GPT teacher head0.282
Teacher spread0.245 · 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 designNot applicable
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".

Quick stats

Citations0
Published2014
Admission routes1
Has abstractyes

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Same venueCINECA IRIS Institutional Research Information System (University of Bari Aldo Moro)French-language works237,207