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Record W2956157517 · doi:10.1080/14649357.2019.1629197

Gigs, Side Hustles, Freelance: What Work Means in the Platform Economy City/ Blight or Remedy: Understanding Ridehailing’s Role in the Precarious “Gig Economy”/ Labour, Gender and Making Rent with Airbnb/ The Gentrification of ‘Sharing’: From Bandit Cab to Ride Share Tech/ The ‘Sharing Economy’? Precarious Labor in Neoliberal Cities/ Where Is Economic Development in the Platform City?/ Shared Economy: WeWork or We Work Together

2019· article· en· W2956157517 on OpenAlexaff
Lisa K. Bates, Austin Zwick, Zachary Spicer, Tamara Kerzhner, Anna Joo Kim, Ashley Baber, Jamaal Green, Dominic Moulden

Bibliographic record

VenuePlanning Theory & Practice · 2019
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsWestern University
Fundersnot available
KeywordsGig economyBATESWork (physics)Farm workersState (computer science)Precarious workEconomySociologyLabour economicsPolitical scienceEconomicsPrecarityLawAgricultureEngineeringHistoryArchaeology

Abstract

fetched live from OpenAlex

Lisa K. Bates Toulan School of Urban Studies and Planning, Portland State University, Portland, OR, USAOver the past year, taxi drivers around the world have protested the appearance of ride-hailin...

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)0.004
metaresearch head score (Gemma)0.005
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: none
Teacher disagreement score0.024
Threshold uncertainty score0.051

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.005
Meta-epidemiology (narrow)0.0010.001
Meta-epidemiology (broad)0.0000.001
Bibliometrics0.0020.002
Science and technology studies0.0150.041
Scholarly communication0.0230.036
Open science0.0020.010
Research integrity0.0050.006
Insufficient payload (model declined to judge)0.0140.003

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 head0.058
GPT teacher head0.262
Teacher spread0.204 · 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

Citations32
Published2019
Admission routes1
Has abstractyes

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