ABSTRACT
The dataset contains information obtained during the analysis and evaluation of the contents of 100 Terms of Service (ToS) of online platforms from the point of view of the European Union consumer law. Each ToS has been assigned information regarding the presence and quality of remedy clauses, dispute resolution clauses, unilateral alteration clauses, rights to police the behavior of users, and regulatory requirements. In addition, descriptions of service features and parties' rights and duties have been pulled out. The sample contains 100 ToS of digital platforms operating in sixteen market sectors: Cloud storage, Communication, Dating, Finance, Food, Gaming, Health, Music, Shopping, Social, Sports, Transportation, Travel, Video, Work, and Various. The selected companies' headquarters span four legal surroundings: the US, the EU, Poland specifically, and other jurisdictions (including, e.g., China, Japan, and the UK). The chosen platforms are both privately held and publicly listed and offer both fee-based and free services. The resulting data table includes 100 observations described by 38 variables (10 metadata and 28 presenting results of the analysis). The definitions of variables and categorical values are presented in the instruction followed by the annotators. All the analyzed ToS in original and annotated form are a part of the dataset. The documents were retrieved from publicly accessible websites of respective online platforms on February 22, 2022, from the territory of Poland, the European Union. Each document was subsequently annotated independently by two researchers, based on the enclosed instruction. The instruction was prepared by the PI, with the help of the team, based on the EU law. The annotators subsequently run consistency checks. The process was designed to ensure the lack of errors and the clarity of the instruction. When ambiguities in the latter were discovered, the PI and the annotators resolved them, and the previously tagged documents were retroactively examined for consistency. These data have significant reuse potential. They can be reused by social scientists attempting to understand the dynamics of the digital markets or normative scholars, like lawyers or political philosophers, attempting to create algorithms for scoring online consumer contracts. They can also be reused by various non-scholarly actors, including policymakers verifying the efficacy of their regulations, developers willing to market their products in a consumer-friendly way, or consumer organizations attempting to raise consumer awareness. The data is suitable for many different types of data analysis methods, such as cluster analysis, dimensionality reduction, classification methods, and scoring.
ABSTRACT
The paper aims to define the variables that elevate the risk of VFL recurrence after adequate primary treatment, and to present the Recurrence Risk Model with practical conclusions to handle pVFL and rVFL. Out of 207 patients with primary vocal fold leukoplakia (pVFL), in 41 (19.8%) recurrent VFL (rVFL) was diagnosed. All patients were assessed by using a trans-nasal flexible video-endoscope using white light, and NBI. The primary measure of our study was to investigate whether morphological features of pVFL in WL, vascular pattern in NBI, and primary histological findings could predict VFL recurrence. To create a model of risk factors, two methods were used: logistic regression and a conditional inference decision tree. The study showed smoking was the factor that significantly and most strongly increased the likelihood of rVFL, as well as the older age groups have a greater odds of rVFL. Types IV, V and VI, according to Ni 2019 classification, were associated with a significantly higher risk of rVFL. The algorithm combining patients' dependent variables and the combination of two classifications improves the predictive value of the presented VFL Recurrence Risk Model.