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Record W4389204974 · doi:10.1177/21568693231213088

The Roots of Social Trauma: Collective, Cultural Pain and Its Consequences

2023· article· en· W4389204974 on OpenAlexaff
Seth Abrutyn

Bibliographic record

VenueSociety and Mental Health · 2023
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsUniversity of British Columbia
Fundersnot available
KeywordsEnculturationHistorical traumaSociologySocial psychologyPsychologyIsolation (microbiology)Mental healthCollective identityIdentity (music)Psychological painSocial identity theorySocial isolationCriminologySocial groupPsychoanalysisPsychiatryPsychotherapistAnthropologyAestheticsLawPolitical science

Abstract

fetched live from OpenAlex

Since Kai Erikson’s landmark study of the devastation of five communities in West Virginia, sociology has leveraged the concept of trauma to describe certain social phenomena. Collective trauma came to refer to the destruction of social infrastructure and the ensuing negative mental health outcomes, while cultural trauma has come to describe the imposition of historical and ongoing attacks by a dominant group on the culture (broadly defined) of a group of people sharing a collective identity. The following article sketches out a theory of social trauma designed to bring these two types of sociological trauma together, highlight their similarities and differences, and unite them by grounding them in the neuroscience of (social) pain. The term trauma, borrowed from medical and psychological study, implies pain, but the sociological version of trauma is best understood as the collectivization and enculturation of social pain, or the evolved negative affective response to separation, rejection, exclusion, and isolation from cherished social objects including statuses. The article concludes by modeling the process by which an event transforms individual social pain into collective social trauma as well as the pathways through which social trauma becomes enculturated in a collective identity. Implications for the sociology of mental health follow.

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 categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.498
Threshold uncertainty score0.913

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 studies0.0010.000
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 head0.041
GPT teacher head0.375
Teacher spread0.334 · 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.

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

Citations31
Published2023
Admission routes1
Has abstractyes

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