Political Bias in the Social Sciences: A Critical, Theoretical, and Empirical Review

Honeycutt, Nathan; Jussim, Lee

doi:10.1007/978-3-031-29148-7_5

Cited by 4 publications

(5 citation statements)

References 133 publications

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“…It has been argued that, because activism prioritizes seeking power to implement political goals, and anything goes when seeking power, activism inherently compromises truth (Haider, 2022). Although political agendas have a long and ugly history of compromising the natural and social sciences (Brothers et al, 2021; Honeycutt & Jussim, 2020, 2023; Krylov, 2021; Martin, 2016; Smith, 2014), whether they inherently do so is beyond the scope of the present paper. Nor is this the place to navigate the nuances of “everything is political” as applied to psychological scholarship, although it is worth stating that, even if everything is political in some senses, this does not liberate scholars to engage in distortions or omissions of inconvenient evidence.…”

Section: The Perils Of a Politicized Science: A Case Studymentioning

confidence: 97%

“…If they are not studied or are understudied, they cannot be ruled out. Similarly, even if alternatives to discrimination can be studied without fear of punishment, but only by researchers who either are members of the underrepresented group or have established reputations as fully committed to social justice as construed by activists, the risk of biased studies and unjustifiably canonized conclusions becomes high (Honeycutt & Jussim, 2020, 2023). As such, the scientific benefits of diversity that come from clashing perspectives, dueling biases, and motivated skepticism will have been lost to psychological science.…”

Section: The Epistemic Consequences Of Politicizing Psychological Sci...mentioning

confidence: 99%

“…In this spirit, it is worth considering some data that can be used to compare academic claims about “diversity, equity, and inclusion” with an assessment of how diverse and how inclusive academia is on one of the dimensions highlighted by Hommel—politics. As we (Honeycutt & Jussim, (2023, p. 98) wrote: Academia skews heavily left and the social sciences skew massively left (Langbert & Stevens, 2022). The skew is so extreme that, to those unfamiliar with the data, claims about the skew may sound like propaganda intended to delegitimize academia.…”

Section: Diversity Equity and The Political Exclusion Of The Vast Maj...mentioning

confidence: 99%

“…Furthermore, different biases are necessary in order to maximize the skeptical vetting that is so crucial to the long-term scientific processes capable of producing valid conclusions (Merton, 1942/1973; Stanovich, 2021). The current political monoculture threatens the ability of psychology to produce valid conclusions on politicized topics (for reviews replete with concrete examples of the canonization of demonstrably false conclusions on politicized topics, see Crawford & Jussim, 2017; Honeycutt & Jussim, 2020, 2023; Martin, 2016; Smith, 2014).…”

Section: Diversity (Broad Form) Can Improve Psychological Sciencementioning

confidence: 99%

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Diversity Is Diverse: Social Justice Reparations and Science

Jussim

2024

Perspect Psychol Sci

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Because the term “diversity” has two related but different meanings, what authors mean when they use the term is inherently unclear. In its broad form, it refers to vast variety. In its narrow form, it refers to human demographic categories deemed deserving of special attention by social justice–oriented activists. In this article, I review Hommel’s critique of Roberts et al. (2020), which, I suggest, essentially constitutes two claims: that Roberts et al.’s (2020) call for diversity in psychological science focuses exclusively on the latter narrow form of diversity and ignores the scientific importance of diversity in the broader sense, and ignoring diversity in the broader sense is scientifically unjustified. Although Hommel’s critique is mostly justified, this is not because Roberts et al. (2020) are wrong to call for greater social justice–oriented demographic diversity in psychology but because Hommel’s call for the broader form of diversity subsumes that of Roberts et al. (2020) and has other aspects critical to creating a valid, generalizable, rigorous, and inclusive psychological science. In doing so, I also highlight omissions, limitations, and potential downsides to the narrow manner in which psychology and the broader academy are currently implementing diversity, equity, and inclusion.

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Section: The Perils Of a Politicized Science: A Case Studymentioning

confidence: 97%

Section: The Epistemic Consequences Of Politicizing Psychological Sci...mentioning

confidence: 99%

Section: Diversity Equity and The Political Exclusion Of The Vast Maj...mentioning

confidence: 99%

Section: Diversity (Broad Form) Can Improve Psychological Sciencementioning

confidence: 99%

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Diversity Is Diverse: Social Justice Reparations and Science

Jussim

2024

Perspect Psychol Sci

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“…Political bias could be easily confused with ideological bias. Since a party is a combination of both an ideology and a political leaning, this bias is related to the inclination of news media or information sources or people to favor one political party, ideology, or perspective over others, impacting the content and presentation of news (Honeycutt and Jussim, 2023).…”

Section: Slant Biasmentioning

confidence: 99%

A systematic review of Hyperpartisan News detection: A Comprehensive Framework for Definition, Detection, and Evaluation

Maggini,

Bassi,

Otero

et al. 2024

Preprint

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Hyperpartisan news detection employs advanced technological methods to identify news articles characterized by extreme bias, reporting information in a highly polarized manner. The spread of such news could lead to detrimental effects in terms of social cohesion and facts-perception. This systematic review delves into the uncharted territory of hyperpartisan news detection, where a conspicuous absence of comprehensive studies has left a void in scholarly discourse. Following the PRISMA methodology, we selected 80 pertinent articles. The paper commences by addressing the inherent challenges arising from disparate and ambiguous definitions of hyperpartisan found in existing literature. Through a meticulous analysis, we propose a refined and comprehensive definition of hyperpartisan news, serving as a foundational framework for subsequent exploration. The review systematically evaluates Non-Deep Learning, Deep Learning (i.e. non-Transformer and Transformer-based methods), and mixed approaches employed in the identification of hyperpartisan content across various studies. By scrutinizing methodologies, algorithms, and key features, we categorize and compare their performances, shedding light on their efficacy and limitations. Furthermore, we conducted an examination of 36 datasets utilized in diverse studies, offering insights into the commonalities and variations in data sources. This inclusive dataset analysis contributes to a nuanced understanding of the challenges faced in the development and validation of hyperpartisan news detection models. This paper not only pioneers the systematic review of hyperpartisan news detection, but also establishes a robust foundation for future research endeavors in this critical domain. We emphasize the necessity of standardized definitions, rigorous evaluation metrics, and shared datasets to advance the field.

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