Hypothetical Constructs

Leising, Daniel; Borgstede, Matthias

doi:10.1007/978-3-319-24612-3_679

Cited by 1 publication

(2 citation statements)

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“…However, personality psychology does have an inherent problem in this regard, which the "harder" sciences (e.g., physics) do not have to the same extent: For many or even most of the phenomena that we as personality psychologists are interested in, terms already exist in the everyday language (e.g., "aggression", "intelligence"). There is thus a risk of increasing confusion rather than clarity when such terms, which already have a semantic web of their own, are also used to denote a scientific construct (Leising & Borgstede, 2020). That is because the new, scientific use of the term will almost certainly diverge from how the same term is used by non-scientists (and the latter is almost never precisely known).…”

Section: Step 2: Common Terminologymentioning

confidence: 99%

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Ten steps toward a better personality science – how quality may be rewarded more in research evaluation

et al. 2022

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This target article is part of a theme bundle including open peer commentaries (https://doi.org/10.5964/ps.9227) and a rejoinder by the authors (https://doi.org/10.5964/ps.7961). We point out ten steps that we think will go a long way in improving personality science. The first five steps focus on fostering consensus regarding (1) research goals, (2) terminology, (3) measurement practices, (4) data handling, and (5) the current state of theory and evidence. The other five steps focus on improving the credibility of empirical research, through (6) formal modelling, (7) mandatory pre-registration for confirmatory claims, (8) replication as a routine practice, (9) planning for informative studies (e.g., in terms of statistical power), and (10) making data, analysis scripts, and materials openly available. The current, quantity-based incentive structure in academia clearly stands in the way of implementing many of these practices, resulting in a research literature with sometimes questionable utility and/or integrity. As a solution, we propose a more quality-based reward scheme that explicitly weights published research by its Good Science merits. Scientists need to be increasingly rewarded for doing good work, not just lots of work.

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Section: Step 2: Common Terminologymentioning

confidence: 99%

“…The language that scientists use to address the phenomena that interest them should be superior to the everyday language in terms of precision. In fact, that is the whole point of scientists having such a language of their own (Leising & Borgstede, 2020). Ideally, that precision should be perfect (i.e.…”

Section: Step 2: Common Terminologymentioning

confidence: 99%