MétaCan
Menu
Back to cohort
Record W2793892865 · doi:10.18357/ijcyfs91201818121

PREPAREDNESS FOR EMANCIPATION OF YOUTH LEAVING ALTERNATIVE CARE IN SERBIA

2018· article· en· W2793892865 on OpenAlexvenueno aff
Anita Burgund Isakov, Jasna Hrnčić

Bibliographic record

VenueInternational Journal of Child Youth and Family Studies · 2018
Typearticle
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
Fundersnot available
KeywordsEmancipationPreparednessFeelingFocus groupPsychologyIndependence (probability theory)Financial independenceSocial psychologyNursingPolitical scienceSociologyMedicinePolitics

Abstract

fetched live from OpenAlex

The process of preparing young people for leaving alternative care is not sufficiently researched in Serbia. In order to define what support is necessary for their successful emancipation, this study of 150 young people in care aims to analyse both their preparedness for leaving alternative care, and whether the type of placement (kinship, foster, or residential) makes a difference to the level of preparedness. A mixed method approach was applied. Quantitatively, questionnaires assessing factors contributing to successful emancipation were administered<strong>.</strong> Qualitatively, transcripts of discussions from 5 focus groups, consisting of a total of 26 participants from all 3 types of placement, were analysed. Most of the youth in the sample indicated they have self-care and housekeeping skills, social skills to make friendships and connections, good grades in school, and aspirations for further schooling and starting a family. However, negative feelings such as disturbance, fear, and sorrow, and a sense of missing support and feeling insufficiently prepared for leaving care were also evident in their answers. Both the focus groups and surveys suggest that the biggest concern with the independence of young people leaving alternative care is financial stability. Several recommendations for ways to influence the system in order to improve outcomes for young people are made.

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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.051
Threshold uncertainty score0.262

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 head0.050
GPT teacher head0.364
Teacher spread0.314 · 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

Citations8
Published2018
Admission routes1
Has abstractyes

Explore more

Same venueInternational Journal of Child Youth and Family StudiesSame topicChild Welfare and AdoptionFrench-language works237,207