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Psychological and social analysis of collective trauma: the enduring lessons learned 20 years after the September 11th, terrorist attacks

2021· article· pt· W3177664198 on OpenAlexaff
Fabiana Marques Barbosa Nasciutti, Mojgan Rahbari-Jawoko

Bibliographic record

VenueReflexão · 2021
Typearticle
Languagept
FieldSocial Sciences
TopicTerrorism, Counterterrorism, and Political Violence
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsHumanitiesTerrorismPolitical sciencePhilosophyLaw

Abstract

fetched live from OpenAlex

Acontecimentos que apresentam uma consequência fatal sobre os civis têm, historicamente, um efeito duradourona psique daqueles que os testemunharam. Os ataques terroristas politizados de 11 de setembro de 2001 nos Estados Unidos foram o evento histórico mais significativo do século 21, com grande repercussão global. Iniciadas por esses incidentes, as ameaças contínuas de terrorismo desde então transformaram as atitudes públicas em dimensão social e política, além de terem impactado a maneira como as pessoas se relacionam tanto dentro dos Estados Unidos quanto globalmente. Este artigo examina criticamente as lições duradouras aprendidas 20 anos após o trágico evento. Para tanto, são discutidos: (i) a resposta psicológica global ao 11 de setembro a partir de uma perspectiva histórico-cultural; (ii) os impactos sociais e sociopolíticos mais amplos; (iii) a interação entre a política de identidade, as preocupações e os riscos de segurança nacional, o preconceito, a exclusão e a intolerância religiosa que os eventos incentivaram nos Estados Unidos e no mundo. Além disso, analisa-se como a mídia social, as informações rápidas e as notícias falsas influenciaram o pensamento crítico em todo o mundo. O artigo explora, particularmente, como o 11 de setembro pode potencialmente afetar a propensão individual ao fundamentalismo religioso, ao preconceito e à intolerância com aqueles que não são familiares.

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 categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.512
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0000.002
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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 head0.115
GPT teacher head0.430
Teacher spread0.315 · 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

Citations1
Published2021
Admission routes1
Has abstractyes

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