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Record W3200738748 · doi:10.25071/2563-3694.77

Sleeping into Wakefulness

2021· article· en· W3200738748 on OpenAlexaffvenueabout
Sasha Askarian, Anjali Appadurai

Bibliographic record

VenueNew Sociology Journal of Critical Praxis · 2021
Typearticle
Languageen
FieldHealth Professions
TopicHomelessness and Social Issues
Canadian institutionsYork University
Fundersnot available
KeywordsSociologyPower (physics)IdeologyRite of passageAestheticsCreativitySubject (documents)PsychologyGender studiesPoliticsSocial psychologyPolitical scienceLawArt

Abstract

fetched live from OpenAlex

This piece is composed of a blend of poetry, social commentary, and collage artwork. It aims to draw connections between sleep and liberation, exploring how deeper levels of rest can draw us toward freedom, not only in our material conditions, but of thought, imagination and spiritual exploration. Using the three stages of the sleep cycle – light sleep, REM sleep and slow wave sleep – as a metaphorical and literal device, this piece explores productivity culture’s limiting effect on our mental and spiritual health; the piece creates poetic connections between the physical phenomena and the mental and spiritual possibilities that lie within each sleep stage. As working people, especially racialized working people, we are subject to generations of sleep deprivation through historical processes of enslavement and forced labour extraction, which translates to many lost years of the higher functions of rest: self-knowledge, memory, creativity and resilience. In today’s highly corporatized economy of neoliberal social relations, all working people are subject to a similar theft of the physical, mental, and spiritual power of deep rest. As racialized women of immigrant families, we draw upon our experience of witnessing firsthand the neoliberal ideology of sleep deprivation and extreme productivity portrayed as a necessary rite of passage for our families to have established belonging, stability and safety in Canada.

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 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)0.005
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.107
Threshold uncertainty score0.999

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.066
GPT teacher head0.471
Teacher spread0.405 · 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 teacher head, not a consensus.

Study designTheoretical or conceptual
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

Citations0
Published2021
Admission routes3
Has abstractyes

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