Taylor & Francis Group
Browse

Measuring trust in maps: development and evaluation of the MAPTRUST scale

dataset
posted on 2024-06-28, 08:20 authored by Timothy J. Prestby

The emergence of deepfake geographies and the growing role that maps play in shaping public opinion on key issues has prompted cartographers to interrogate the concept of map trust. However, this growing area of research is hampered by inconsistent and untested measures of map trust. This study addresses this critical gap by developing and validating a numerical rating scale that exclusively measures map trust. A model of map trust consisting of specific indicators is derived from an exploratory factor analysis. This model is then evaluated using a confirmatory factor analysis. The results indicate that map trust can be explained from a single factor related to veracity and reliability. Two factors pertaining to bias and appearance did not explain enough variance in the model. Findings also suggest that map trust can be measured by having participants evaluate maps according to twelve empirically-derived indicators: accurate, correct, error-free, honest, trustworthy, credible, fair, reliable, reputable, objective, authentic, and balanced. Measurement validity and reliability assessments of this new scale are not only based on theory but are also empirically validated. This scale can be a useful tool for researchers and practitioners alike to measure an individual’s trust in maps.

Funding

This material is based upon work supported by the National Science Foundation Graduate Research Fellowship Program under [Grant No. DGE1255832]. Any opinions, findings, and conclusions or recommendations expressed in this material are those of the author(s) and do not necessarily reflect the views of the National Science Foundation. We also gratefully acknowledge the financial support of the Penn State Geography Department via the Gregory Knight Endowment of Geography and the GeoGraphics Lab.

History

Usage metrics

    International Journal of Geographical Information Science

    Licence

    Exports

    RefWorks
    BibTeX
    Ref. manager
    Endnote
    DataCite
    NLM
    DC