MétaCan
Menu
Back to cohort
Record W4230868087 · doi:10.32920/ryerson.14657100

The Rise of Uber and the [Re]construction of the North American Dream

2021· preprint· en· W4230868087 on OpenAlexaff
Tori Zenko

Bibliographic record

Venuenot available
Typepreprint
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsToronto Metropolitan University
Fundersnot available
KeywordsNarrativeDreamMeaning (existential)AestheticsSociologyHistoryPolitical sciencePsychologyArtEpistemologyPhilosophyLiterature

Abstract

fetched live from OpenAlex

The road – while on the surface often perceived as merely a means of allowing individuals to move from one location to another, has during recent decades become deeply intertwined with both individual and mass narratives related to the pursuit of freedom. The freedom narrative began when the United States highway system, developed during the early 1960s and thematically charged by the Beat Generation’s road-trip literature, became imbued with new meaning and new freedom-facilitating potential. The road, an architectural feat once thought of largely as a means of providing mass mobilization, came to be understood as both the road to freedom, and the road as freedom. However, today we find ourselves experiencing a new road narrative, one that still speaks to freedom but that differs vastly from the road narratives of the 1960s. Today, as individuals experience the road through sharing-economy services such as Uber, a narrative shift has occurred whereby freedom on the road is no longer experienced individualistically and/or destructively but, instead, communally and constructively.

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)0.003
metaresearch head score (Gemma)0.002
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: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.063
Threshold uncertainty score0.125

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0030.002
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0160.021
Scholarly communication0.0100.012
Open science0.0010.006
Research integrity0.0020.005
Insufficient payload (model declined to judge)0.0090.001

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 head0.010
GPT teacher head0.189
Teacher spread0.179 · 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

Citations0
Published2021
Admission routes1
Has abstractyes

Explore more

Same topicSharing Economy and PlatformsFrench-language works237,207