Replication Data for: O IMPACTO DA PANDEMIA DE COVID-19 NA ATUAÇÃO DA BUROCRACIA DE NÍVEL DE RUA NO BRASIL

The data used in this article were collected using an instrument (survey) that sought to map the working conditions of street-level bureaucrats on the front lines of the COVID-19 pandemic. The glossary below summarizes all the variables present in the database and indicates which ones were used to construct the analysis of this article. The binary variables are coded as 0 = No and 1 = Yes. It should be noted that between the 1st and 2nd round of research, new questions were added. Questionnaires are also adapted for each policy. In terms of data analysis in the case of closed questions, the statistics presented in this article are purely descriptive, since they can only be seen as a kind of evaluation of the “interviewed” population (that is, 3,842 valid responses and subgroups). Based on the premise that all interviewees are street-level bureaucrats, the comparison is made proportionally in relation to each professional universe through contingency tables and graphs. The results do not allow for statistical inference, but describe an overview of more than 3,000 street-level bureaucrats in the context of the current pandemic. Concomitantly, we performed a qualitative analysis of open responses, based on the categorization of data for content analysis (Bardin, 1994; Saldaña, 2009)

本文所用数据通过调研工具（survey）采集，旨在勾勒新冠疫情防控一线街头官僚（street-level bureaucrats）的工作状况图景。下文的变量术语表汇总了数据库中的全部变量，并指明了本文分析环节所采用的变量。二分变量的编码规则为0代表「否」、1代表「是」。需要说明的是，在第一与第二轮调研之间，新增了若干调研问题；同时问卷针对不同政策场景进行了适配调整。针对封闭式问题的数据分析中，本文呈现的统计结果均为纯描述性统计，此类统计仅可作为对「受访群体」（即3842份有效应答及对应子群体）的评估依据。基于「所有受访对象均为街头官僚」这一前提，本文通过列联表与统计图，结合各职业群体的基准总量开展比例化对比。本研究结果无法支持统计推断，但完整呈现了新冠疫情背景下逾3000名街头官僚的工作概况。与此同时，基于内容分析法（content analysis）的数据分类框架，本文对开放式调研应答开展了质性分析（Bardin, 1994; Saldaña, 2009）