scholarly journals The role of recoding in implicit social cognition: Investigating the scope and interpretation of the ReAL model for the implicit association test

PLoS ONE ◽  
2021 ◽  
Vol 16 (4) ◽  
pp. e0250068
Author(s):  
Jimmy Calanchini ◽  
Franziska Meissner ◽  
Karl Christoph Klauer

The ReAL model is a multinomial processing tree model that quantifies the contribution of three qualitatively distinct processes–recoding, associations, and accuracy–to responses on the implicit association test (IAT), but has only been validated on a modified version of the IAT procedure. The initial goal of the present research was to validate an abbreviated version of the ReAL model (i.e., the Brief ReAL model) on the standard IAT procedure. Two experiments replicated previous validity evidence for the ReAL model on the modified IAT procedure, but did not produce valid parameter estimates for the Brief ReAL model on the standard IAT procedure. A third, pre-registered experiment systematically manipulated all of the task procedures that vary between the standard and modified IAT procedures–response deadline, number of trials, trial constraints–to determine the conditions under which the Brief ReAL model can be validly applied to the IAT. The Brief ReAL model estimated theoretically-interpretable parameters only under a narrow range of IAT conditions, but the ReAL model generally estimated theoretically-interpretable parameters under most IAT conditions. We discuss the application of these findings to implicit social cognition research, and their implications to social cognitive theory.

2019 ◽  
Author(s):  
Michael McCarthy

After two decades of research on implicit social cognition, it has become clear many of the field's theories and practices need to be redressed. Addressed in the present paper are the assumptions and memetic ideas embedded in the language, theory, and measurement tools of so-called implicit social cognition, their historical and contemporary shortcomings, and solutions to avoid these shortcomings and improve scholarship in this field. Specifically, the present paper recommends researchers and theorists adopt more accurate and epistemically honest language in their work, and determine what measures of implicit social cognition measure through experimental research rather than through empirically unjustifiable assumptions. Contributing to this endeavour, the present paper includes an experiment testing whether performance on the Implicit Association Test (IAT) can be changed through the indirect activation of complex associations. Here it is demonstrated that performance on IAT appears to be unaffected by indirectly activated complex associations, ruling out a possible cognitive mechanism that could contribute to performance on the IAT.


Author(s):  
Ottavia M. Epifania ◽  
Egidio Robusto ◽  
Pasquale Anselmi

<p>The advent of implicit measures opened the access to processes of which people might not be completely aware but that can still influence their attitudes, preferences, and behaviors towards different objects. Among the existing implicit measures, the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) is one of the most studied and used. The descriptive literature review presented in this work was aimed at providing an overview of how the IAT has been used from the year of its first introduction until current days. Specifically, the main fields of application of the IAT, the specific topics for which it has been used, and its concurrent use with other implicit measures have been highlighted and described. When possible, information on the samples on which the studies were carried out are reported. Results indicate an on-going growth of the IAT in a constantly wider range of topics. The ability of the IAT to overcome self-presentation biases and to access the implicit aspects of attitudes have been particularly exploited for investigating biases towards different out-groups, especially in sensitive contexts.<br></p>


2020 ◽  
Author(s):  
Ottavia M. Epifania ◽  
Egidio Robusto ◽  
Pasquale Anselmi

<p>The advent of implicit measures opened the access to processes of which people might not be completely aware but that can still influence their attitudes, preferences, and behaviors towards different objects. Among the existing implicit measures, the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, 1998) is one of the most studied and used. The descriptive literature review presented in this work was aimed at providing an overview of how the IAT has been used from the year of its first introduction until current days. Specifically, the main fields of application of the IAT, the specific topics for which it has been used, and its concurrent use with other implicit measures have been highlighted and described. When possible, information on the samples on which the studies were carried out are reported. Results indicate an on-going growth of the IAT in a constantly wider range of topics. The ability of the IAT to overcome self-presentation biases and to access the implicit aspects of attitudes have been particularly exploited for investigating biases towards different out-groups, especially in sensitive contexts.<br></p>


2015 ◽  
Vol 46 (1) ◽  
pp. 46-54 ◽  
Author(s):  
Franziska Meissner ◽  
Klaus Rothermund

In 2001, Brendl and colleagues reported a reversed compatibility effect for an insect-nonword Implicit Association Test (IAT), apparently indicating more positive attitudes for insects than for neutral nonwords and therefore calling into question the validity of the IAT. According to a prominent alternative account of IAT effects, this reversed effect reflects task recoding based on salience asymmetries. To disentangle the contributions of associations and recoding, we analyzed data of an insect-nonword IAT with the ReAL model and discovered that (1) recoding is responsible for the unexpected direction of this IAT effect and (2) insects still activated negative associations. Applying the ReAL model helps to avoid misleading interpretations of IAT effects by providing independent estimates for different processes within an IAT.


2016 ◽  
Author(s):  
Brian A. Nosek ◽  
Mahzarin R. Banaji

Overview=======The GNAT (pronounced like the bug) is a flexible technique designed to measure implicit social cognition. Conceptually similar to other implicit measures like the Implicit Association Test (IAT; Greenwald, McGhee, & Schwartz, JPSP, 1998), the GNAT assesses automatic associations between concept (e.g., gender) and attribute (e.g., evaluation) categories. The GNAT has two features that distinguish it from other measures of implicit social cognition. First, the GNAT is designed to be use signal detection statistics in its calculation of automatic associations (d-prime), but can also be adapted to utilize response latency as its operational dependent variable. Second, the GNAT is flexible in the establishing of contextual characteristics for the evaluative situation. For example, the IAT requires an attitude toward one category (insects) be assessed relative to a second category (flowers). With the GNAT, experimenters can vary whether insects are evaluated in the context of a single category (flowers), a superordinate category (animals), a generic category (objects) or with no context at all.


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