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Record W2468368803 · doi:10.1111/fcre.12231

1‐800‐Skype‐Me

2016· article· en· W2468368803 on OpenAlexaboutno aff
Andrea Himel, Hon. Debra Paulseth, Jessica Cohen

Bibliographic record

VenueFamily Court Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Dynamics and Relationships
Canadian institutionsnot available
Fundersnot available
KeywordsVariety (cybernetics)Mode (computer interface)PsychologyComputer scienceHuman–computer interaction

Abstract

fetched live from OpenAlex

It is increasingly common that children of divorce are geographically separated from one of their parents. This article considers the challenges that arise from that reality by exploring this problem from a variety of perspectives and by providing practical tips to minimize the impact of the distance. A review of the Ontario caselaw and Arizona Guidelines reveal that certain factors are important in the resolution of these disputes, including: the age of the child, mode of transportation between homes, distance, prior contact, and feasibility of virtual access. Court‐ordered access may include remedies that, absent the distance issue, may be considered extreme, including moving to overnight/extended access periods for young children, permitting children to travel unaccompanied, favoring the nonresident parent for holidays and vacation time, allowing children to decrease contact with the nonresident parent, and decreasing or terminating child support. Where distance dictates the in‐person and virtual access schedules, creative solutions are critical to the successful resolution of these cases. Forward thinking family law professionals can meaningfully help parents to achieve better outcomes for children.

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)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.893
Threshold uncertainty score0.152

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.000
Scholarly communication0.0010.001
Open science0.0010.002
Research integrity0.0020.001
Insufficient payload (model declined to judge)0.8930.712

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 head0.046
GPT teacher head0.333
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 source (direct Gemma or distilled Codex), not a consensus.

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

Citations3
Published2016
Admission routes1
Has abstractyes

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