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Record W3047453087 · doi:10.1016/j.dib.2020.106129

Cumulative risk and protection measures data

2020· article· en· W3047453087 on OpenAlexafffund
Bianca C. Bondi, Debra Pepler, Mary Motz, Naomi C. Z. Andrews

Bibliographic record

VenueData in Brief · 2020
Typearticle
Languageen
FieldPsychology
TopicChild Abuse and Trauma
Canadian institutionsBrock UniversityYork University
FundersCanadian Institutes of Health Research
KeywordsCumulative riskPsychosocialPsychologyMental healthIntervention (counseling)Clinical psychologyDevelopmental psychologyMedicinePsychiatry

Abstract

fetched live from OpenAlex

These data include clinically and theoretically grounded, cross-domain cumulative risk and protection measures. These measures were established for use with three sibling groups at Mothercraft's Breaking the Cycle (BTC), a child maltreatment prevention and early intervention program for substance using mothers and their children. These measures were established using archival data obtained from clients' charts. The cumulative risk factor measure encompasses: 1) items from a cumulative risk measure utilized in prior BTC research, 2) clinical measures assessing maternal mental health, addiction, and parenting capacity, 3) a measure utilized in studies on adverse childhood experiences, and 4) the Diagnostic Classification of Mental Health and Developmental Disorders of Infancy and Early Childhood (Axis IV: Psychosocial Stressors) [1-3]. The cumulative protection factor measure encompasses: 1) existing early intervention components of services at BTC, 2) clinical measures assessing maternal mental health, addiction, and parenting capacity, and 3) known protective factors outlined in the literature. Both measures were theoretically grounded using the Developmental Model of Transgenerational Transmission of Psychopathology [4], which enabled salient domains of risk and protection to be delineated for children exposed prenatally to substances and accessing child maltreatment prevention and early intervention services. For a description of the process of establishing these measures, the total and cross-domain cumulative risk and protection percentages for the sample, as well as a qualitative interpretation of the balance between domains of risk and protection, see [5]. These measures can contribute to improved future understanding around cumulative risk and cumulative protection in vulnerable populations, salient domains of risk and protection, and the unique interaction that occurs between risk and protective processes in the context of child maltreatment prevention and early intervention.

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)0.014
metaresearch head score (Gemma)0.081
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: Not applicable
GenreCandidate signal: Dataset · Consensus signal: Dataset
Teacher disagreement score0.075
Threshold uncertainty score0.252

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0140.081
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0100.009
Science and technology studies0.0020.001
Scholarly communication0.0030.003
Open science0.0030.004
Research integrity0.0010.003
Insufficient payload (model declined to judge)0.0750.024

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 head0.205
GPT teacher head0.357
Teacher spread0.152 · 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
GenreDataset

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

Citations8
Published2020
Admission routes2
Has abstractyes

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