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Record W2725170968

Culture and Trauma among War Affected Communities

2012· book· en· W2725170968 on OpenAlexaboutno aff
Ousmane Bakary Bâ

Bibliographic record

VenueLAP LAMBERT Academic Publishing eBooks · 2012
Typebook
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsnot available
Fundersnot available
KeywordsRacializationCriminalizationCriminologyRacismRefugeeSociologyGender studiesAcculturationPovertyPolitical scienceEthnic groupRace (biology)LawAnthropology
DOInot available

Abstract

fetched live from OpenAlex

This book includes two major parts. The first studies the interdisciplinary theoretical, methodological and the empirical perspectives of Ethnoanthropology, Sociology and Social work as they approach Culture, Identity,Trauma and Bereavement experiences among war affected African refugee communities.The second part focuses on affected African communities: Impacts of trauma on their social integration issues and on their Refugee youth’s involvement in gangs (Winnipeg, Manitoba) and provides a relevant anthropological analysis of crucial social and cultural issues faced by these communities.This book mainly reveals the systemic racism and exclusion, the racial profiling and criminalization mechanisms targeting War affected African refugee communities and the Black Youth in general. The suppression and coercion strategies deployed by the Criminal Justice System purposefully ignore the traumatic backgrounds of such wounded youth and their real life experiences of war exile, survival and their socioeconomic distress deeply worsened by the permanent institutional and structural racialization of their poverty and their cultural marginalization.

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 machine prediction

Teacher imitation

Not calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.

metaresearch head score (Codex)0.000
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.006
Threshold uncertainty score0.018

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0040.003
Scholarly communication0.0040.002
Open science0.0010.002
Research integrity0.0010.002
Insufficient payload (model declined to judge)0.0050.001

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 head0.031
GPT teacher head0.295
Teacher spread0.264 · 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 source (direct Gemma or distilled Codex), 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

Citations0
Published2012
Admission routes1
Has abstractyes

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