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Record W7028479833

Exploring stories of trust from foster youth in college

2023· dissertation· en· W7028479833 on OpenAlexfundno aff

Bibliographic record

VenueK-State Research Exchange (Kansas State University) · 2023
Typedissertation
Languageen
FieldSocial Sciences
TopicChild Welfare and Adoption
Canadian institutionsnot available
FundersMcGill University
KeywordsDistrustNarrativeQualitative researchFoster careNarrative inquiryLived experience
DOInot available

Abstract

fetched live from OpenAlex

This narrative study explores the experiences of five college students who were formerly involved with foster care. This study explores the ways former foster youth students tell stories of trust built or trust broken with adults before and during college. The data analysis revealed themes that add to the body of research by providing a clearer understanding of the experiences students share about trust-building or distrust throughout childhood and college. Themes identified before college include: covering up home life during childhood, distrust in biological family, shifting trust to an adult outside of the family, and a revolving door of adults as a barrier to trust building. Themes identified during college include: trusting professors, building boundaries with others, and ongoing management of family status. Finally, participants shared living between trust in self and needing reassurance throughout college. By contributing to the current literature, higher education professionals are encouraged to use these findings to advocate for full-time staff and nuanced programming for foster youth. University leaders are encouraged to use these findings to ensure the needed supports are in place for each student.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.287
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0020.003
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0010.000
Research integrity0.0000.001
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 head0.256
GPT teacher head0.353
Teacher spread0.096 · 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 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

Citations0
Published2023
Admission routes1
Has abstractyes

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