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Record W3026140281 · doi:10.1037/tra0000739

Mitigating social and economic sources of trauma: The need for universal basic income during the coronavirus pandemic.

2020· article· en· W3026140281 on OpenAlex
Matthew Johnson, Elliott Johnson, Laura Webber, Daniel Nettle

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenuePsychological Trauma Theory Research Practice and Policy · 2020
Typearticle
Languageen
FieldPsychology
TopicMigration, Health and Trauma
Canadian institutionsInstitute of Population and Public Health
Fundersnot available
KeywordsUnemploymentPandemicRecessionSocial distanceCoronavirus disease 2019 (COVID-19)PsycINFOShock (circulatory)Great DepressionDevelopment economicsPolitical science2019-20 coronavirus outbreakSevere acute respiratory syndrome coronavirus 2 (SARS-CoV-2)Basic incomeEconomicsEconomic growthMedicineVirologyMEDLINEKeynesian economicsLaw

Abstract

fetched live from OpenAlex

The COVID-19 pandemic is projected to cause an economic shock larger than the global financial crisis of 2007-2008 and a recession as great as anything seen since the Great Depression in 1930s. The social and economic consequences of lockdowns and social distancing measures, such as unemployment, broken relationships and homelessness, create potential for intergenerational trauma extending decades into the future. In this article, we argue that, in the absence of a vaccine, governments need to introduce universal basic income as a means of mitigating this trauma. (PsycInfo Database Record (c) 2020 APA, all rights reserved).

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.

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)0.004
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.720
Threshold uncertainty score0.873

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.001
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 head0.238
GPT teacher head0.499
Teacher spread0.261 · 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