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Record W2955521095 · doi:10.17645/mac.v7i2.1817

Board Games as Interview Tools: Creating a Safe Space for Unaccompanied Refugee Children

2019· article· en· W2955521095 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

fundA Canadian funder is recorded on the work.
no affNo Canadian affiliation: this work is invisible to an affiliation-only frame.
No Canadian affiliation. An affiliation-only frame, the usual design, would never have seen this work. It is one of the works that make the case for inverting the frame.

Bibliographic record

VenueMedia and Communication · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicEducation and experiences of immigrants and refugees
Canadian institutionsnot available
FundersYork University
KeywordsBespokeRefugeeSociologyVisual researchPhoto elicitationSpace (punctuation)Public relationsMedia studiesPolitical scienceComputer scienceVisual artsLaw

Abstract

fetched live from OpenAlex

Since the emergence of the new sociology of childhood in the late 1980s, there has been an increasing expectation to engage children actively and to take their views seriously throughout the research process. This is even more important when it comes to unaccompanied refugee children, whose voice is seldom heard. In this article the author builds upon her project of exploring unaccompanied refugee children’s lived media experiences and argues that—in order to have meaningful results and to create safe spaces for those who need it most—we need to search beyond traditional research tools. Specifically, she proposes to bring into research the concept of “play”. The article presents the use of bespoke, artisanal board games in cross-national interview settings with unaccompanied refugee children. It is argued that these creative tools can help in collecting diverse and rich data that can successfully complement traditional research methods

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.

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: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.845
Threshold uncertainty score0.351

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.028
GPT teacher head0.335
Teacher spread0.306 · 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