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Where vulnerability can become a strength: A focused ethnography of a community program for youth exposed to violence

2018· article· en· W2808587186 on OpenAlexaffabout
Marjorie Montreuil, Jean‐Frédéric Ménard, Franco A. Carnevale

Bibliographic record

VenueChildren and Youth Services Review · 2018
Typearticle
Languageen
FieldHealth Professions
TopicCommunity Health and Development
Canadian institutionsUniversité de SherbrookeMcGill UniversityDouglas Mental Health University Institute
Fundersnot available
KeywordsVulnerability (computing)EthnographyPsychologySociologyCriminologyForensic engineeringComputer securityEngineeringComputer scienceAnthropology

Abstract

fetched live from OpenAlex

There is developing evidence that more effective means for preventing violence should involve social development programs for youths. A focused ethnographic study was conducted over 8 months in a social development program situated in Montreal (Quebec, Canada), aimed at providing support to youths who have been exposed to violence as actors, recipients, or witnesses. The study included participant observation, interviews with youths and staff members, and a review of documents, to examine how the program operates socially and how these social processes affect youths favorably and unfavourably. Youths' experiences with the program were meaningful by permitting them to examine and reflect on who they are, what they have experienced and how to “connect” with others. The safe social space that was created by the youths and coordinators allowed for this meaningful engagement with the program, which led to outcomes that could go beyond the program itself and affected youths' relationships with others, their self-perception, as well as their mental wellbeing . The program contributed to help manage some of the difficulties youths were facing.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.635
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.000
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 head0.093
GPT teacher head0.420
Teacher spread0.327 · 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 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

Citations7
Published2018
Admission routes2
Has abstractyes

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