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Record W3035326514 · doi:10.5539/res.v12n3p9

Growth of Sharing Economy in Hungary; Long Distance Car Sharing - A Case Study of Oszkár

2020· article· en· W3035326514 on OpenAlexvenueno aff
Kinga Szabó, Gauri Shankar Gupta

Bibliographic record

VenueReview of European Studies · 2020
Typearticle
Languageen
FieldBusiness, Management and Accounting
TopicSharing Economy and Platforms
Canadian institutionsnot available
Fundersnot available
KeywordsSharing economyParadigm shiftReputationConstruct (python library)BusinessAccommodationEconomyEconomicsPolitical scienceLawComputer science

Abstract

fetched live from OpenAlex

Rapid growth of sharing economy in the last two decades is the outcome of a paradigm shift in global capitalism and societal values. Based on digital identity and the Trust and Reputation Index, IT platforms have brought together strangers who under new social construct, share under-utilized capacities and assets with those who need them. Radius of trust which was initially confined to family and friends; now encompasses strangers who speak no common language and who live oceans apart. Hungary is no exception to this global shift. Sharing economy in Hungary has registered healthy growth specially in the areas of transportation and accommodation. Oszkár, a long-distance car-sharing company presents a good example of this paradigm shift in societal values and sharing with strangers. This platform has recorded impressive growth of over 67% between 2015-2018 with very positive customer reviews. Moreover, this represents an environmentally-friendly sustainable practice which successfully reduces carbon foot-print and traffic congestion.

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: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.262
Threshold uncertainty score0.627

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0000.000
Science and technology studies0.0000.000
Scholarly communication0.0000.001
Open science0.0000.001
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 head0.083
GPT teacher head0.280
Teacher spread0.197 · 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 designObservational
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

Citations2
Published2020
Admission routes1
Has abstractyes

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