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Record W2980423739 · doi:10.1093/ccc/tcz026

A Desirable Future: Uber as Image-Making in Winnipeg

2019· article· en· W2980423739 on OpenAlexafffundabout
Sheri Gibbings, J. Andrew Taylor

Bibliographic record

VenueCommunication Culture and Critique · 2019
Typearticle
Languageen
FieldEngineering
TopicTransportation and Mobility Innovations
Canadian institutionsWilfrid Laurier University
FundersWilfrid Laurier University
KeywordsVisionThe ImaginaryReputationWhite (mutation)IndigenousSociologySociotechnical systemThe SymbolicPower (physics)Media studiesPolitical scienceManagementSocial science

Abstract

fetched live from OpenAlex

Abstract This paper investigates the sociotechnical imaginary surrounding Uber’s supposedly imminent arrival in Winnipeg, through an examination of communication in the public sphere. We examine how actors mobilized their communicative resources in efforts to either bring ride-hailing or keep it away. For some advocates, ride-hailing technology was less important than Uber’s symbolic value of building Winnipeg’s image as an innovative city. Media coverage contrasted innovation and Uber with Winnipeg’s anxieties about being behind other cities and its taxi industry’s reputation as stuck in the past. These visions of Winnipeg’s future addressed an unspoken White, middle-class city dweller. While Winnipeg’s transportation industry was shaped by the socially located experiences of racialized immigrant men as taxi drivers and Indigenous women as passengers, these actors had less power to shape the imaginary. Our analysis suggests that cities like Winnipeg view Uber as an image-making product as much as a beneficial service for their citizens.

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)0.000
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: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.816
Threshold uncertainty score0.325

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.000
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 head0.007
GPT teacher head0.264
Teacher spread0.257 · 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 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

Citations4
Published2019
Admission routes3
Has abstractyes

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