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Record W4402072717 · doi:10.1080/21647259.2024.2384201

Unspeakable: reflections on relational approaches to research in post-conflict settings

2024· article· en· W4402072717 on OpenAlexaff
Erin Baines

Bibliographic record

VenuePeacebuilding · 2024
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsFutures contractDemobilizationPsychologySociologySocial psychologyCriminologyPoliticsPolitical scienceLaw

Abstract

fetched live from OpenAlex

In this article, I offer reflections on a research project with former combatants who fathered children as the result of conflict-related sexual violence in northern Uganda. The research sought to understand how becoming a father shaped their decision making as soldiers, and reintegration experiences following demobilisation. What roles, if any, do they play in their children’s lives post-conflict, and what futures do they envision for them? I consider the ethical and methodological challenges of the research project through the concept of the unspeakable, what Judith Herman refers to as ‘traumatic events that take place outside socially validated reality.’ How does one come to know beyond what one can imagine, or that which is socially unrecognisable, such as the love of fathers associated with the perpetration of violent atrocities? I foreground a relational approach to the research encounter, one that fostered intimate, steadfast, and mutually giving relationships between the research team and participants, and opening pathways to explore intimacy between a father and child. I then reflect on what this methodology offers in terms of thinking beyond Western-centric conceptualizations of peacebuilding.

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)0.002
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.858
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0020.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.001

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 head0.448
GPT teacher head0.478
Teacher spread0.029 · 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.

Study designNot applicable
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

Citations1
Published2024
Admission routes1
Has abstractyes

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