MétaCan
Menu
Back to cohort
Record W2003565398 · doi:10.12927/hcq.2014.24017

Caring for Caregivers of High-Needs Children

2014· article· en· W2003565398 on OpenAlexaff
Allie Peckham, Karen Spalding, Jillian Watkins, Cindy Bruce-Barrett, Marta Grasic, A. Paul Williams

Bibliographic record

VenueHealthcare Quarterly · 2014
Typearticle
Languageen
FieldPsychology
TopicFamily and Disability Support Research
Canadian institutionsHospital for Sick Children
Fundersnot available
KeywordsNursingCase managementMedicineCase managerKey (lock)Medical homePsychologyProcess managementPrimary careBusinessFamily medicineComputer science

Abstract

fetched live from OpenAlex

The Caregiver Framework for Children with Medical Complexity, led by the Hospital for Sick Children, is a ground-breaking initiative that validates and supports the vital role of unpaid, family caregivers. The project uses a supported self-management model that includes a modest amount of funding to address pressing needs, and relies on Key Workers who provide ongoing education, counselling and care management to assist caregivers in planning over the longer-term. This paper describes the findings from a multi-stage, mixed-methods evaluation to examine the design and outcomes of the Caregiver Framework.

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)0.000
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.580
Threshold uncertainty score0.984

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.031
GPT teacher head0.348
Teacher spread0.317 · 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 teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
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

Citations27
Published2014
Admission routes1
Has abstractyes

Explore more

Same venueHealthcare QuarterlySame topicFamily and Disability Support ResearchFrench-language works237,207