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Record W2514986365 · doi:10.3138/ctr.167.005

Risk and Resilience: Models for Personal Finance and the Arts

2016· article· en· W2514986365 on OpenAlexvenueaboutno aff
Natasha Mytnowych

Bibliographic record

VenueCanadian Theatre Review · 2016
Typearticle
Languageen
FieldEconomics, Econometrics and Finance
TopicCommunity Development and Social Impact
Canadian institutionsnot available
Fundersnot available
KeywordsWorkforceThe artsWork (physics)Psychological resiliencePublic relationsFace (sociological concept)Creative industriesResilience (materials science)SociologyBusinessVisual artsPolitical scienceEconomic growthEngineeringArtEconomicsPsychologySocial scienceSocial psychology

Abstract

fetched live from OpenAlex

The arts sector has long been a precarious workforce, cobbling together short contracts and part-time gigs, and practitioners face the considerable challenge of balancing time for artistic practice and meeting financial needs. Natasha Mytnowych surveys the obstacles facing artists and creative workers in Canada, uncovering the specifics of what an individual artist or arts worker must do outside of paid hours to keep their lives, their creative practice, and in turn, the sector, afloat, especially as it becomes harder and harder to secure paid artistic work. Mytnowych advocates for new perspectives on arts labour, in particular the importance of de-stigmatizing work outside of one’s primary artistic practice; she recommends recognizes additional work as a legitimate and necessary financial supplement to the pursuit of risky, non-commercial creative projects. Mytnowych also notes that, as the rest of the workforce is becoming more similar to the creative sector, there are opportunities to create resources and practices to help entrepreneurs, contract workers, and others juggling multiple types of employment.

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)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Review · Consensus signal: none
Teacher disagreement score0.853
Threshold uncertainty score0.996

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.040
GPT teacher head0.241
Teacher spread0.202 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designNot applicable
Domainnot available
GenreReview

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

Citations1
Published2016
Admission routes2
Has abstractyes

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