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Privacy or Self-Censorship? Coping Strategies of Young Polish Job Candidates under Cybervetting

Author

Listed:
  • Pawełoszek Ilona

    (Department of Management Information Systems, Czestochowa University of Technology, Częstochowa, Poland)

  • Niedbał Rafał

    (Department of Management Information Systems, Czestochowa University of Technology, Częstochowa, Poland)

Abstract

Purpose The article investigates how young adults in Poland (aged 18–30) adjust their self-presentation on social media in response to cybervetting. It compares two strategies—preventive profile privacy settings and reactive self-censorship—across professional and general platforms. It also explores whether the amount of time spent online correlates with the intensity of these actions. Design/methodology/approach An online survey (conducted March–April 2025) was completed by 126 respondents. Ordinal scales measured the level of profile privacy and frequency of self-censorship. Due to significant deviations from normal distribution, the Mann–Whitney U test was used. The relationship between time spent online and strategies was assessed using Spearman’s correlation. Findings Users of professional platforms reported stricter privacy settings; self-censorship did not differ. Time spent online was not related to self-censorship but was slightly negatively correlated with privacy settings. Research limitations/implications. Self-reported measures, simplified platform classification, non-random sampling, and lack of demographic subgroup analysis limit generalizability. Originality/value This is one of the first studies in Poland to compare preventive and reactive strategies toward cybervetting across platform types, combining impression management and context collapse theories. It shows that platform type, versus time online, drives privacy choices.

Suggested Citation

  • Pawełoszek Ilona & Niedbał Rafał, 2026. "Privacy or Self-Censorship? Coping Strategies of Young Polish Job Candidates under Cybervetting," International Journal of Contemporary Management, Sciendo, vol. 62(1), pages 51-61.
    • Handle: RePEc:vrs:ijcoma:v:62:y:2026:i:1:p:51-61:n:1004
    DOI: 10.2478/ijcm-2026-0004
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    References listed on IDEAS

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    1. da Motta Veiga, Serge P. & Figueroa-Armijos, Maria, 2022. "Considering artificial intelligence in hiring for cybervetting purposes," Industrial and Organizational Psychology, Cambridge University Press, vol. 15(3), pages 354-356, September.
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      JEL classification:

      • J24 - Labor and Demographic Economics - - Demand and Supply of Labor - - - Human Capital; Skills; Occupational Choice; Labor Productivity
      • M54 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Personnel Economics - - - Labor Management
      • M15 - Business Administration and Business Economics; Marketing; Accounting; Personnel Economics - - Business Administration - - - IT Management
      • O33 - Economic Development, Innovation, Technological Change, and Growth - - Innovation; Research and Development; Technological Change; Intellectual Property Rights - - - Technological Change: Choices and Consequences; Diffusion Processes

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