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Record W3010714048 · doi:10.7202/1068123ar

Chapter 3

2020· article· en· W3010714048 on OpenAlexvenueno aff
Adele Baruch, Daniel Creek

Bibliographic record

VenueNarrative Works · 2020
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsnot available
Fundersnot available
KeywordsTheme (computing)Natural disasterAction (physics)Collective actionHurricane katrinaSociologyNatural (archaeology)PsychologyRecallSocial psychologyPublic relationsHistoryPolitical scienceLawGeographyPoliticsArchaeology

Abstract

fetched live from OpenAlex

The special circumstances related to helping in the aftermath of Hurricane Katrina—both a natural disaster and a man-made catastrophe—are explored. Stories of individual, formal, and informal networks of helping, alongside stories of exploitation and despair, were shared by participants. Significant to the history of the aftermath of Katrina was the eventual formalizing of some of the informal helping networks, such as the establishment of a musician’s village and performance center in the 9th Ward of New Orleans. The theme of “doing the right thing” echoed throughout our participant interviews, as did “the chance to move beyond angry.” Stories of helping appeared to provide examples of hope to the citizens affected by the storm, as well as encouragement towards purposeful action. The stories of helping, along with participation in altruistic social networks, appear to provide a pathway to the recollection and transformation of traumatic memories.

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)0.003
Version: metacan-v3-hybrid-931329e0061cValidation 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: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.537
Threshold uncertainty score0.000

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.003
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0030.001
Scholarly communication0.0070.004
Open science0.0020.004
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.4630.245

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 head0.037
GPT teacher head0.305
Teacher spread0.268 · 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.

Study designNot applicable
Domainnot available
GenreOther

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

Citations0
Published2020
Admission routes1
Has abstractyes

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