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Record W2902788431 · doi:10.1080/10522158.2019.1546809

Social work practice with war-affected children and families: the importance of family, culture, arts, and participatory approaches

2018· article· en· W2902788431 on OpenAlexaffabout
Myriam Denov, Meaghan Shevell

Bibliographic record

VenueJournal of Family Social Work · 2018
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsMcGill University
Fundersnot available
KeywordsRefugeePsychosocialMental healthCitizen journalismContext (archaeology)Social workDiversity (politics)The artsSociologyPopulationPublic relationsPsychologyPolitical scienceGender studiesEconomic growthPsychiatryGeographyLaw

Abstract

fetched live from OpenAlex

War and armed conflict not only gravely impact individual children, but the entire family system, with the impacts of war further compounded by the complexities of displacement, flight, migration, and resettlement to new contexts. These processes can cause destabilizing ruptures in the social fabric, networks, and services that support and protect children and families, ultimately hindering their potential protective capacities and potentially contributing to negative long-term intergenerational effects. The family plays a vital role in shaping children‘s mental health and well-being in conflict and post conflict settings, and thus the family needs to be accorded greater consideration in designing psychosocial support services for war-affected populations. With growing numbers of war-affected refugees resettling in Canada and the U.S., it is critical that psychosocial programs and interventions address their unique needs, as individuals, families, and communities. Moreover, there is a greater need for culturally responsive practice with war-affected refugee children and families that accounts for the diversity and heterogeneity of their needs and lived experiences. In this Special Issue entitled: “Children of War and their Families: Perspectives on Social Work Practice & Education”, we suggest that factors such as fostering a family approach, allotting careful attention to context and culture, alongside an emphasis on linking the arts and participation with social work practice, can be key social work contributions to research, education, and practice with this important and often overlooked population.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.554
Threshold uncertainty score0.637

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.082
GPT teacher head0.355
Teacher spread0.274 · 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 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

Citations44
Published2018
Admission routes2
Has abstractyes

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