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Record W3197913151 · doi:10.25071/2563-3694.80

What's Safe

2021· article· en· W3197913151 on OpenAlexaffvenueabout
Melika Hashemi, Maryanne Casasanta, Lauren Runions, Heddy Graterol

Bibliographic record

VenueNew Sociology Journal of Critical Praxis · 2021
Typearticle
Languageen
FieldSocial Sciences
TopicGeographies of human-animal interactions
Canadian institutionsInstitute for Christian StudiesUniversity of Toronto
Fundersnot available
KeywordsImprovisationCourageDanceSociologyRelation (database)Space (punctuation)DistancingSocial distanceSocial changeProductivityAestheticsMedia studiesVisual artsPsychologyPublic relationsPolitical scienceArtLawCoronavirus disease 2019 (COVID-19)Computer scienceEconomic growth

Abstract

fetched live from OpenAlex

What’s Safe is an ongoing response to Toronto’s social distancing measures. It is a dance score documented cinematically in Trinity Bellwoods Park, with movements inspired by Deepa Iyer’s framework (Mapping Our Roles in Social Change Ecosystems, 2020) and Jay Pitter’s open letter to Canadian urbanists (A Call to Courage, 2020). The project was conceived, performed, and captured by the authors of this paper. The two dancers, our second and third authors, engage in creative problem-solving by facing the reality of socially-distant grounds for play and suggesting a different type of productivity, one which is conducive to individual and social growth. The movements are then captured by our multimedia creator (or fourth author), while our artist-researcher (first author) curates and provides critique throughout. The final project considers artistic practice in response to social change as informed by (un)productivity. It uses productive imagination (e.g., play, improvisation, creative problem-solving) to investigate parameters of safety (e.g., surveillance, control, space). Through the dancers’ improvisations, we attempt to navigate these tensions and better position ourselves in relation to our current socio-geographical circumstances.

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)0.007
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: none
Teacher disagreement score0.655
Threshold uncertainty score0.995

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.007
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.002
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0060.000

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 head0.043
GPT teacher head0.409
Teacher spread0.366 · 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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Same venueNew Sociology Journal of Critical PraxisSame topicGeographies of human-animal interactionsFrench-language works237,207