MétaCan
Menu
Back to cohort
Record W3137665330 · doi:10.1177/0020872820969781

Peace, love, and justice: A participatory phenomenological study of psychosocial well-being in Afghanistan

2021· article· en· W3137665330 on OpenAlexaff
Martha Bragin, Bree Akesson, Mariam Ahmady, Sediqa Akbari, Bezhan Ayubi, Raihana Faqiri, Zekrullah Faiq, Spozhmay Oriya, Rohina Zaffari, Mohammad Hadi Rasooli, Basir Ahmad Azizi, Fareshteh Barakzai, Yasamin Haidary, Sediqa Jawadi, Hannah Wolfson, Sayed Jafar Ahmadi, Basir Ahmad Karimi, Sataruddin Sediqi

Bibliographic record

VenueInternational Social Work · 2021
Typearticle
Languageen
FieldPsychology
TopicResilience and Mental Health
Canadian institutionsWilfrid Laurier University
FundersUnited States Agency for International Development
KeywordsOperationalizationAfghanPsychosocialContext (archaeology)Citizen journalismSociologyBiopsychosocial modelPsychologySocial psychologyPolitical sciencePsychotherapistEpistemologyGeographyLaw

Abstract

fetched live from OpenAlex

While there have been many studies that elucidate the extent of human suffering in Afghanistan, there has been no formal study of what it means to be psychologically and socially well. This article reports on a participatory phenomenological study conducted in Afghanistan designed to better understand psychosocial well-being. Collecting data from 440 Afghan participants in 56 focus group discussions, the research specifically elaborated and operationalized definitions of psychosocial well-being that were relevant to the Afghan context. This study adds critical value around definitions of what it means to be psychosocially well in Afghanistan and other conflict-affected countries.

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)0.019
metaresearch head score (Gemma)0.018
Version: metacan-v3-hybrid-931329e0061cValidation 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 score0.030
Threshold uncertainty score0.101

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0190.018
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.002
Science and technology studies0.0300.026
Scholarly communication0.0060.006
Open science0.0020.011
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0030.000

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 head0.052
GPT teacher head0.435
Teacher spread0.383 · 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 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
Published2021
Admission routes1
Has abstractyes

Explore more

Same venueInternational Social WorkSame topicResilience and Mental HealthFrench-language works237,207