Cited by 11Social and Intergroup PsychologyPsychometric Methodologies and TestingMigration, Refugees, and Integration

A measure of positive and negative perception of migration: Development and psychometric properties of the Positive and Negative Perception of Immigrants Scale (PANPIS)

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Panno, Angelo, Pellegrini, Valerio, De Cristofaro, Valeria, Donati, Maria Anna·2023·Analyses of Social Issues and Public Policy

Abstract

This paper reports the validation and psychometric properties of the Positive and Negative Perception of Immigrants Scale (PANPIS)—a new measure to assess positive and negative attitude towards immigrants. Across two studies ( N = 956), the psychometric evidence of the PANPIS is presented. As expected, exploratory factor analysis suggested a two factors and 14‐item structure, which was ratified using a confirmatory factor analysis. Corroboration of the measure's robustness was provided by a multigroup‐CFA, which yielded evidence for the gender invariance of the measure (Study 1). Study 2 showed measurement invariance of the online version with respect to the paper‐and‐pencil version. Reliability, discriminant, and criterion validities were examined across Studies 1 and 2 showing satisfactory results for both paper‐and‐pencil and online versions, respectively. These results suggest that the PANPIS is a psychometrically sound measure having the distinctive characteristic to simultaneously investigate prejudice by capturing both positive and negative attitudes towards immigrants.

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  • AI systems exhibit network externality: the larger the data network they access, the more intense their training.

    “AI systems exhibit this network externality too: the larger the data network they access, the more intense their training (LeCun et al., 2015;Panno et al., 2023).”

    From Deepfakes, Democracy, and the Ethics of Synthetic Media: A Synthesis of the SOLARIS Project (2026) · cites this paper as Panno et al., 2023

    The Introduction discusses attitudes toward immigrants, and the Reliability and validity section evaluates the PANPIS scale. Searches for AI network externalities, training data, and machine learning found no passage addressing the claim. The available passages provide neither support nor a contrary finding. (LLM, conf=0.78)

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Authors
Panno, A., Pellegrini, V., De Cristofaro, V., & Donati, M. A.
Affiliations
  • European University of Rome (IT)
  • Sapienza University of Rome (IT)
  • Department of Social and Developmental Psychology Sapienza University of Rome Rome Italy
  • University of Florence (IT)
Corresponding author
Panno, Angelo
Venue
Analyses of Social Issues and Public Policy
Publisher
Wiley
Published
2023-02
Volume
23
Issue
1
Pages
73-105
ISSN
  • 1529-7489 (ISSN-L)
  • 1530-2415
OpenAlex
W4319808062
Cited by
11
References
1
Citations by year
2026: 5 · 2025: 3 · 2024: 1 · 2023: 1 · 2022: 1
FWCI
4.30
Type
journal article
Language
en
Open access
Locations
  • Analyses of Social Issues and Public Policy (publishedVersion, cc-by)
  • Florence Research (University of Florence) (submittedVersion, other-oa)
  • IRIS Research product catalog (Sapienza University of Rome) (submittedVersion, cc-by)
  • Archivio Istituzionale della Ricerca - Università degli Studi della Campania "Luigi Vanvitelli" (submittedVersion)
Topics
  • Social Sciences › Sociology and Political Science › Social and Intergroup Psychology
  • Social Sciences › Decision Sciences › Management Science and Operations Research › Psychometric Methodologies and Testing
  • Social Sciences › Sociology and Political Science › Migration, Refugees, and Integration
Keywords
attitudes toward immigrants, scale development, psychometric validation, measurement invariance, gender invariance, prejudice, factor structure

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