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Record W3105418340 · doi:10.1177/1473325020973316

Where has vulnerability gone?

2020· article· en· W3105418340 on OpenAlex
Catherine Phillips

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

VenueQualitative Social Work · 2020
Typearticle
Languageen
FieldPsychology
TopicLeadership, Courage, and Heroism Studies
Canadian institutionsLakehead University
Fundersnot available
KeywordsVulnerability (computing)SociologyPoliticsNarrativeSocial vulnerabilityVulnerability assessmentEnvironmental ethicsPolitical scienceSocial psychologyPsychologyPsychological resilienceLawComputer security

Abstract

fetched live from OpenAlex

During Covid-19, health care workers have been vulnerable to death, and at the same time, in response to their vulnerability, heroic. Heroism is one of the most ubiquitous narratives during this pandemic. In this article, I am interested in the juncture between vulnerability and heroism, the discursive privileging of a hero and the implications of this for social workers in health and social care. I use the writings of Judith Butler to ask, where has vulnerability gone? I argue that it is not that vulnerability is erased or suppressed, or comes second in the public imaginary, but rather, vulnerability is reconstituted as heroic and becomes unrecognisable. Vulnerability is an under-examined concept in social work and an analysis of its cultural representation during the outbreak of Covid-19, can contribute to our knowledge about how vulnerability operates in health and social care, as well as how vulnerability conditions the cultural spaces we operate within. Can new insights, provoked by the cultural responses to this pandemic, lead to a reorientation for social work politics and the politics of vulnerability?

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesInsufficient payload (model declined to judge)
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.544
Threshold uncertainty score0.998

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0040.002

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 head0.285
GPT teacher head0.447
Teacher spread0.162 · 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