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Record W2586274745 · doi:10.1921/swssr.v18i3.956

Engagement tactics with foster parents: Experiences of resource workers

2016· article· en· W2586274745 on OpenAlexaff
Jason Brown, Sarah Serbinski, Julie Gerritts, Landy Anderson

Bibliographic record

VenueSocial Work and Social Sciences Review · 2016
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsWestern University
Fundersnot available
KeywordsFoster careSet (abstract data type)Resource (disambiguation)WelfarePsychologyAccountabilityMetropolitan areaSocial workWork (physics)Foster parentsSocial psychologySociologyMedicineNursingPolitical scienceEconomic growthComputer scienceEconomics

Abstract

fetched live from OpenAlex

Resource workers are child welfare workers who work closely with foster parents following placement of a child placed in care. One of the challenges they experience is reluctance to their involvement. Resource workers from a large metropolitan area were asked: “What do you do when foster parents are reluctant about your involvement?” Responses to this question were analyzed with multidimensional scaling and cluster analysis. Nine concepts resulted, including: Recognize Problems, Build Trust, Go the Extra, Be Positive, Broaden their Network, Find Commonalities, Set Limits, Understand Them, and Reinforce Accountability. These concepts were compared and contrasted with the available literature.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.802
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0030.002
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 head0.054
GPT teacher head0.341
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 teacher head, not a consensus.

Study designNot applicable
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

Citations1
Published2016
Admission routes1
Has abstractyes

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