Sharing Data in the Platform Economy: A Public Interest Argument for Access to Platform Data
Pourquoi ce travail est dans la base
Une base qui oublie comment elle a trouvé un travail ne peut pas être vérifiée. Voici les voies qui ont admis celui-ci.
Notice bibliographique
Résumé
Airbnb is a ‘sharing economy’ platform that facilitates the booking of short-term accommodation. The company is premised on the idea that many urban dwellers have excess space – rooms in homes or apartments – or have space they do not use at certain periods of the year (entire homes or apartments while on vacation, for example) – and that a digital marketplace can maximise efficient use of this space by matching those seeking temporary accommodation with those having excess space. This characterization of Airbnb is open to challenge. Indeed, a number of studies, including ones by the Canadian Centre for Policy Alternatives, the City of Vancouver, and the NY State Attorney General suggest that a significant number of units for rent on Airbnb are offered as part of commercial enterprises. The description also belies Airbnb’s disruptive impact. The process of re-characterization and commodification of ‘surplus’ private spaces neatly evades the regulatory frameworks designed for the marketing of short-term accommodation and leaves licensed short-term accommodation providers complaining that their highly regulated businesses are being undermined by competition from those not bearing the same regulatory burdens. At the same time, the data that would otherwise be captured through regulatory processes is effectively privatized in the hands of Airbnb, which retains exclusive control over it. This poses a challenge to local and regional governments who regulate and tax short-term accommodation in the public interest. This paper explores the impact on cities of platform companies such as Airbnb from the perspective of data. It argues that platform-based short-term rental activities have a fundamental impact on what data are available to municipal governments who struggle to regulate in the public interest. The impacts of platform companies are therefore not just disruptive of incumbent industries; they are disruptive of planning and regulatory systems by masking activities and creating data deficits. Cities need to find solutions to this data deficit. Currently available solutions range from self-help type recourses such as data scraping, or entering into data-sharing agreements with the platform companies. Each of these has its challenges and drawbacks. Further action may be required by governments to ensure their data needs are adequately met, and the paper addresses some of these options.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,006 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,000 |
| Études des sciences et des technologies | 0,001 | 0,000 |
| Communication savante | 0,008 | 0,020 |
| Science ouverte | 0,013 | 0,004 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découle