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Record W7112905474

(Un)regulation of extraordinary expenses for children in family crises: comparative insights from the canadian model

2024· article· en· W7112905474 on OpenAlexaboutno aff

Bibliographic record

VenueNova Science Publishers (Nova Science Publishers, Inc.) · 2024
Typearticle
Languageen
FieldSocial Sciences
TopicConflict of Laws and Jurisdiction
Canadian institutionsnot available
Fundersnot available
KeywordsDiscretionAppealLegislationNormativePerspective (graphical)Balance (ability)Best practice
DOInot available

Abstract

fetched live from OpenAlex

The regulation of extraordinary expenses in separation and divorce proceedings represents a critical challenge in Italian Family Law. The absence of centralized legislation and uniform guidelines has resulted in fragmented practices across courts, amplifying judicial discretion and generating uncertainty for parents. This article provides the results of a systematic mapping of the protocols adopted by Italian courts, revealing significant disparities in the management of extraordinary medical, educational, and extracurricular expenses, both nationally and within individual Court of Appeal Districts. Conversely, drawing on the Canadian model, which employs federal uniform guidelines to regulate extraordinary expenses, this study investigates how such an approach can balance certainty, predictability, fairness, and flexibility. Employing a methodology that integrates inductive and deductive approaches – including case study analysis and a review of normative and doctrinal sources from a comparative perspective – therefore, the article proposes actionable recommendations to harmonize Italian practices, aiming to reduce legal uncertainty and improve outcomes for families.

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)0.007
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies, Scholarly communication
Consensus categoriesScience and technology studies, Scholarly communication
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.636
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.013
Science and technology studies0.0030.009
Scholarly communication0.0140.035
Open science0.0040.000
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 head0.086
GPT teacher head0.348
Teacher spread0.262 · 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 designObservational
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
Published2024
Admission routes1
Has abstractyes

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