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Record W3134610343 · doi:10.1177/1473325020973344

Pandemic disruptions: The subversion of neoliberalism

2021· article· en· W3134610343 on OpenAlexaff
Nancy Ross

Bibliographic record

VenueQualitative Social Work · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicSocial Work Education and Practice
Canadian institutionsDalhousie University
Fundersnot available
KeywordsNeoliberalism (international relations)PandemicAction (physics)SociologyTragedy (event)Collective actionSocial distanceRacismGlobePublic relationsPolitical sciencePolitical economyCoronavirus disease 2019 (COVID-19)Gender studiesSocial sciencePoliticsPsychologyLawMedicine

Abstract

fetched live from OpenAlex

The implications of the COVID 19 pandemic signal both tragedy and possibility. This reflective paper considers the amplification of the concurrent pandemics of violence against women and children and anti-black racism during the responses to COVID 19 and renewed calls to action. The enforced 'pause' as a result of social isolation or distancing measures in response to COVID-19, has led many people to re-imagine a different world and ignited social movements across the globe. Education must inspire a vision of what our world could be and define what action is needed and the steps required to implement change. The critical reflection that characterizes most social work educational programs can provide opportunities to harness such imaginings in redefining 'the possible' in the quest for a more equitable and safer world. This article describes the potential of the pandemic to subvert the pervasive influence of neoliberalism by promoting collective notions of care.

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)0.021
metaresearch head score (Gemma)0.016
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.021
Threshold uncertainty score0.110

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0210.016
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.001
Science and technology studies0.0120.087
Scholarly communication0.0100.011
Open science0.0020.016
Research integrity0.0030.007
Insufficient payload (model declined to judge)0.0030.000

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 head0.128
GPT teacher head0.483
Teacher spread0.356 · 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 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

Citations7
Published2021
Admission routes1
Has abstractyes

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