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Record W2589305965 · doi:10.3126/jpan.v4i1.16735

Resilience among people who face natural disaster

2017· article· en· W2589305965 on OpenAlexaff
Avinash De Sousa, Amresh Shrivastava

Bibliographic record

VenueJournal of Psychiatrists Association of Nepal · 2017
Typearticle
Languageen
FieldSocial Sciences
TopicDisaster Management and Resilience
Canadian institutionsLawson Health Research Institute
Fundersnot available
KeywordsResilience (materials science)ConvictionFace (sociological concept)InstinctPsychological resiliencePower (physics)PsychologySociologySocial psychologyPolitical scienceSocial scienceLawEcology

Abstract

fetched live from OpenAlex

Human beings possess the power to resist an adverse situation and this unique characteristic is one of the basic instinct to survive. Individual capacity to deal with insurmountable adversities is a matter of great astonishment. Often physical capacity fails but drive and conviction to survive in difficult situations persist and remains source of strength. In language of understanding it is referred to an internal capacity to fight. A number of people refer to this as ‘resilience’. There are about seventy definitions of the term resilience. The Oxford dictionary defines it as ‘the capacity to recover quickly from difficulties and toughness’. Considering most of the references to tern resilience it appears to be ‘human capacity to deal with adverse situations and quickly bounce back to normalcy’.

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)0.000
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.008
Threshold uncertainty score0.026

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0020.001
Scholarly communication0.0010.002
Open science0.0000.003
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0080.001

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 head0.008
GPT teacher head0.304
Teacher spread0.296 · 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 designObservational
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

Citations7
Published2017
Admission routes1
Has abstractyes

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