Airbnb como urbanismo de plataforma: aspectos gerais e caminhos para uma abordagem multiescalar
Bibliographic record
Abstract
This article presents aspects highlighted in scientific studies on Airbnb as an expression of “platform urbanism” and indicates processes that can be observed in socio-spatial and economic dynamics stimulated by short-term rentals worldwide, aiming to formulate paths for a multi-scalar investigation. To achieve this, the article is divided into three parts. In the first part, we analyze studies on Airbnb encompassing the concept of platform urbanism and indicating the main aspects they point out. In the second part, events related to Airbnb activities in five countries (United States, Mexico, Canada, Japan, and China) are presented, gathered from newspaper news. And in the third part, four processes related to these events are listed: the complexification of the real estate system; new flows defined by digital nomadism; new arrangements in the private sector; and the expansion of vacation rental companies according to pre-existing political and economic logics.
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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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.006 | 0.006 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".