Although such methodological innovations are perceived to be beneficial 11 for qualitative enquiries, the reliability of quantitative social studies became threatened 12. The availability of respondents decreased and data collection in many studies was moved online 7, 8, 9 however, the adaptation strategies, regarding both study designs and sampling, were often applied independently by individual researchers 10. All social science researchers, even those who had been working within the pre-Big Data paradigms 1, have been compelled to adapt their well-established methodologies to new conditions. More recently, the outbreak of the COVID-19 pandemic has further complicated the landscape for scholars across disciplines. Despite the undeniable benefits of the increasing availability of secondary data 2, 3, 4, the widespread datafication process 5 has raised many ethical 6 and epistemological 1 concerns. The growing prominence of data-driven inquiries in social sciences has been widely debated for over a decade 1. We have demonstrated that, in crisis conditions such as COVID-19, the proposed method can serve as a proxy for a multi-level recognition of PA conflict potentials, provided that it synthesises the results of different methodological approaches, followed by in-person interviews in the selected case studies. Although the reported conflict issues corresponded to the indicator-derived descriptors of the cluster, in the theory-driven phase of the assessment, the state register failed to address the key prerequisites of PA conflicts. For one cluster, we juxtaposed the obtained results with secondary data from another source (Internet content) and for a specific PA (Tatra National Park). We distinguished five types of PA conflict determinants in Lesser Poland (‘urbanity’, ‘agriculture’, ‘tourism’, ‘small-scale entrepreneurship’, and ‘sprawl’) and respective groups of 15 clusters comprising local-level units. With the ultimate aim to inform case study selection, we processed 187 relevant indicators from the official Statistics Poland register for a Lesser Poland region. To address this need in the field of protected area (PA) conflict analysis, we propose a three-fold approach (theory-, method-, and cross-scale simulation-driven) to assess the usefulness of the utilized state register dataset and the indicator analysis methodology for the multi-level recognition of PA conflict determinants. ![]() This evoked doubts about the validity of the results unless restrictive assessment procedures are implemented. Recently, a global trend towards a broader use of secondary data in social sciences has been reinforced by the COVID-19 pandemic.
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