Growth of Sharing Economy in Hungary; Long Distance Car Sharing - A Case Study of Oszkár
Bibliographic record
Abstract
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.
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot 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.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.002 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 0.000 |
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.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
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".