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Record W1554012002 · doi:10.1017/cbo9780511500008

Understanding Trauma

2007· book· en· W1554012002 on OpenAlexaff
Laurence J. Kirmayer, Robert Jay Lifton, Vinuta Rau, Mark E. Bouton, Gregory J. Quirk, Mark Barad, Rosemary C. Bagot, J. Douglas Bremner, Emeran A. Mayer, Elna Yadin, J. David Kinzie, Arieh Y. Shalev, Bessel A. van der Kolk, Derrick Silove, James K. Boehnlein, Cécile Rousseau, Melvin Konner, Allan H. Young, Gadi BenEzer

Bibliographic record

VenueCambridge University Press eBooks · 2007
Typebook
Languageen
FieldPsychology
TopicAcademic and Historical Perspectives in Psychology
Canadian institutionsMcGill University
Fundersnot available
KeywordsTraumatic stressPerspective (graphical)Psychological resilienceSection (typography)Variety (cybernetics)Affect (linguistics)PsychologyVulnerability (computing)Social psychologyClinical psychologyCommunication

Abstract

fetched live from OpenAlex

This book analyzes the individual and collective experience of and response to trauma from a wide range of perspectives including basic neuroscience, clinical science, and cultural anthropology. Each perspective presents critical and creative challenges to the other. The first section reviews the effects of early life stress on the development of neural systems and vulnerability to persistent effects of trauma. The second section of the book reviews a wide range of clinical approaches to the treatment of the effects of trauma. The final section of the book presents cultural analyses of personal, social, and political responses to massive trauma and genocidal events in a variety of societies. This work goes well beyond the neurobiological models of conditioned fear and clinical syndrome of post-traumatic stress disorder to examine how massive traumatic events affect the whole fabric of a society, calling forth collective responses of resilience and moral transformation.

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)0.001
metaresearch head score (Gemma)0.001
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.017
Threshold uncertainty score0.058

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.001
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.008
Scholarly communication0.0050.007
Open science0.0010.003
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0170.004

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 head0.123
GPT teacher head0.301
Teacher spread0.177 · 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 designTheoretical or conceptual
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

Citations221
Published2007
Admission routes1
Has abstractyes

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