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Record W4387503837 · doi:10.37559/meac/23/08

Partners in Peace Research: Participatory Research Training Pilot with Young People in Mosul, Iraq

2023· report· en· W4387503837 on OpenAlexfundno aff
Sajad Jiyad, Schadi Semnani, MEHDI SHAKARCHI, Siobhan O'Neil

Bibliographic record

Venuenot available
Typereport
Languageen
FieldHealth Professions
TopicHealth and Conflict Studies
Canadian institutionsnot available
FundersGlobal Affairs CanadaEidgenössisches Departement für Auswärtige AngelegenheitenUNICEF
KeywordsParticipatory action researchFocus groupCitizen journalismQualitative researchBridge (graph theory)Pilot programTraining (meteorology)Medical educationPsychologyPolitical scienceGender studiesSociologyGeographyMedicineSocial science

Abstract

fetched live from OpenAlex

This new MEAC Research Fieldwork Note delves into a pilot qualitative training program for youth researchers in Mosul. Working with local NGO Bridge, this programme sought to equip conflict-affected youth with research skills and prepare them to co-facilitate focus groups with their peers. The goal of this pilot programme was to find a way for young

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)0.020
metaresearch head score (Gemma)0.010
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Other · Consensus signal: none
Teacher disagreement score0.020
Threshold uncertainty score0.108

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0200.010
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0110.003
Scholarly communication0.0030.002
Open science0.0020.008
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0110.002

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 head0.954
GPT teacher head0.717
Teacher spread0.237 · 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 designNot applicable
Domainnot available
GenreOther

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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