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Record W4412883800 · doi:10.1080/17450128.2025.2539730

Reconstructing the final narrative: <i>how psychological autopsies reconstruct the final narratives of youth across diverse sociocultural context</i>

2025· article· en· W4412883800 on OpenAlexaff
Matias Gay

Bibliographic record

VenueVulnerable Children and Youth Studies · 2025
Typearticle
Languageen
FieldPsychology
TopicIdentity, Memory, and Therapy
Canadian institutionsCapital District Health Authority
Fundersnot available
KeywordsNarrativeSociocultural evolutionContext (archaeology)SociologyGender studiesPsychologyHistoryAnthropologyLiteratureArtArchaeology

Abstract

fetched live from OpenAlex

Youth suicide is a leading cause of death worldwide, with Indigenous and marginalized youth disproportionately affected. While traditional psychological autopsy studies tend to emphasize psychiatric diagnoses, they often fail to capture the narrative, cultural, and existential dimensions that shape suicidality. This study draws on 21 psychological autopsy investigations of youth aged 10 to 25, using narrative identity theory, existential suicidology, and models such as McAdams’ narrative identity theory and Galynker’s Suicide Crisis Syndrome to explore the deeper contours of suicidal risk. The findings suggest that suicide in youth frequently follows a trajectory marked by cumulative adversity, fractured identity, and ruptured relationships. Common themes included a loss of belonging, untreated psychological pain, cultural disconnection, and the foreclosure of personal narrative. Many youth had encountered healthcare services but remained unseen or unsupported in ways that addressed the meaning-making and relational aspects of their distress. Rather than viewing suicide solely as a psychiatric outcome, the study proposes reframing it as a breakdown in narrative coherence and existential grounding. A more humane and effective approach to prevention and care will require integrating narrative-informed, culturally sensitive frameworks into early intervention, postvention, and mental health systems more broadly.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.065
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0030.003
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.089
GPT teacher head0.374
Teacher spread0.285 · 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 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

Citations4
Published2025
Admission routes1
Has abstractyes

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