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Record W1974035175 · doi:10.1155/2012/796763

Intervention to Prevent Child Custody Loss in Mothers with Schizophrenia

2011· article· en· W1974035175 on OpenAlexaff
Mary V. Seeman

Bibliographic record

VenueSchizophrenia Research and Treatment · 2011
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsCanada Research ChairsUniversity of Toronto
Fundersnot available
KeywordsMental healthPsychological interventionIntervention (counseling)PsychiatryMedicineJurisdictionMental illnessSchizophrenia (object-oriented programming)PopulationNursingPsychologyEnvironmental healthPolitical science

Abstract

fetched live from OpenAlex

Depending on jurisdiction, time period studied, and specifics of the population, approximately 50 percent of mothers who suffer from schizophrenia lose custody of their children. The aim of this paper is to recommend interventions aimed at preventing unnecessary custody loss. This paper reviews the social work, nursing, psychology, psychiatry, and law literature on mental illness and custody loss, 2000-2011. Recommendations to mothers are to (a) ensure family health (b) prevent psychotic relapse, (c) prepare in advance for crisis, (d) document daily parenting activities, (e) take advantage of available parenting resources, and f) become knowledgeable about legal issues that pertain to mental health and custody. From a policy perspective, child protection and adult mental health agencies need to dissolve administrative barriers and collaborate. Access to appropriate services will help mothers with schizophrenia to care appropriately for their children and allow these children to grow and develop within their family and community.

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)0.001
metaresearch head score (Gemma)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Non-randomized trial · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.005
Threshold uncertainty score0.011

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0030.000

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 head0.051
GPT teacher head0.340
Teacher spread0.289 · 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 designNon-randomized trial
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

Citations80
Published2011
Admission routes1
Has abstractyes

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