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Record W2791510657 · doi:10.18357/ijcyfs91201818124

CREATING FUTURES: RESIDENTIAL CARE HOMES IN HUNGARY AND SWITZERLAND COLLABORATIVELY DEVELOP THEIR CAPACITY TO EMPOWER CHILDREN AND YOUTH TO ACTIVELY REALISE THEIR OWN FUTURES

2018· article· en· W2791510657 on OpenAlexvenueno aff
A. Allan Schmid, Krisztián Herczeg

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicFamily Support in Illness
Canadian institutionsnot available
Fundersnot available
KeywordsFutures contractEmpowermentContext (archaeology)Public relationsSustainabilitySociologyBusinessPolitical sciencePsychologyGeography

Abstract

fetched live from OpenAlex

Child and youth homes in Hungary and Switzerland want to increase the chances that the approximately 1,000 children and youth in their care will transition well from residential care to other settings, will be fully included in society, and will live lives that they have reason to value. Key to this objective is the empowerment of the children and youth to take their development into their own hands, to develop ideas of a possible future, and to pursue these ideas actively and sustainably. In the project “Creating Futures”, these homes plan to collect knowledge from children, youth, staff, and managers, as well as from the literature; to develop a framework of analysis to identify current good practices, and potentials for further development; and to implement a concrete pilot project in each home. Evaluations of the learning and development process and dissemination of publications complete the project. Throughout, there will be a strong focus on the voice of children and youth. Collaborating as a community of practice and within the context of expert network FICE International, the homes will make use of their diversity for stimulating learning and development on the individual, professional, and organisational levels. This paper describes the emergence and design of the planned project.

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)0.001
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.411
Threshold uncertainty score0.772

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.001
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 science0.0000.000
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 head0.026
GPT teacher head0.306
Teacher spread0.280 · 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 designQualitative
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

Citations3
Published2018
Admission routes1
Has abstractyes

Explore more

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