Inequalities in income, wealth, and opportunities are rampant both between and within nations around the world. Making strides to rectify inequalities requires examining how people come to understand them as well as the psychological processes that translate those understandings into reparative actions. There is some evidence for a “comparative framing effect,” in which the group that is initially referenced impacts judgements by communicating salient information and the appropriate reference point. Research on this comparative framing effect suggests that focusing on disadvantage, relative to advantage, leads to a more negative assessment and intentions to engage in action to reduce the inequality. 

 

In two pilot studies (reported in the current proposal) focused on global inequalities (low-income vs high-income countries), Schnepf et al. (2023) did not find evidence for a main effect of framing on perceived legitimacy of the inequality or intentions to engage in action. They did, however, find some evidence for an interaction with the perceived size of the inequality. When the low-income country was the subject of the comparison, larger perceptions of the size of the inequality were associated with greater intentions to engage in action (both studies) and greater perceptions of the differences as illegitimate (Study 1 only). Moreover, they found some evidence in both studies that negative social emotions such as guilt and shame were the mechanism that explained why perceiving greater inequality in the low-income framing condition was associated with the outcomes. 

 

In the current study, Schnepf et al. (2023) build upon these two pilot studies to conduct a high-quality replication and a stronger test of their hypotheses. Most notably, the proposed Registered Report uses a much larger sample, providing adequate statistical power to detect relatively small interaction effects. Additionally, the proposed project manipulates the size of the inequality that is being evaluated, rather than relying on participants’ perceptions. Finally, the study includes “justice sensitivity,” or the degree to which individuals assess inequality as unfair as an additional hypothesized moderator, and “social dominance orientation” as an exploratory moderator. Along with the pilot studies, the proposed project will represent a strong test of several hypotheses relevant to many different areas of social and personality psychology. 

 

The Stage 1 manuscript was evaluated over two rounds of in-depth peer review, both of which consisted of substantial comments from two scholars with relevant expertise. Based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and was therefore awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/pgyvw
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:

 

 

 

1. Schnepf, J., Reese, G., Bruckmüller, S., Braun, M., Rotzinger, J., & Martiny, S. E. (2023). Justice in the eye of the beholder: How comparison framing affects the perception of global inequality through social emotions and justice sensitivity. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/pgyvw

Everyday decisions can often be biased by how different options are presented and which choices were made previously, over and above whichever option is rationally preferable. Two such major biases in judgment and decision-masking are status quo bias and the default effect. The status quo bias reflects a tendency for people to choose an option that has already been implemented or represents the current state of affairs (for instance, choosing to remain with a current energy supplier rather than switching to a different one, even when the current supplier provides less value for money), while the default effect is a bias toward taking a course of action that would occur automatically in the absence of an active choice (such as the pre-selected energy supplier in questionnaire). Status quo bias and default effects can overlap or diverge: the status quo option will often be the same as the default, while on other occasions the default option in a choice set will be determined by other factors and differ from the option that was already implemented.

 

In the current study, Yam and Feldman (2023) propose a replication and extension of an influential study by Dinner et al. (2011) that purported to examine default effects but, arguably, actually studied its nearby cousin, status quo bias. Using a large online sample, the authors will independently test for the existence of both status quo bias and the default effect, before then asking whether (and if so how) status quo bias and default effects interact and how they are related to several potential explanatory variables, including perceived effort (which may be lower for the status quo or default) and endorsements (whether through direct recommendations or indirectly through perceived norms). The authors also build in additional manipulation checks and comprehension checks, in addition to exploratory analyses examining (among other variables), the political orientation of participants.

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review. Based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/ep3jh
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 

References
 

1. Dinner, I., Johnson, E. J., Goldstein, D. G., & Liu, K. (2011). Partitioning default effects: Why people choose not to choose. Journal of Experimental Psychology: Applied, 17, 332– 341. https://doi.org/10.1037/a0024354

2. Yam, M. L. M.  & Feldman, G. (2023). Reference points and decision-making: Impact of status quo and defaults in a conceptual replication and extensions Registered Report of Dinner et al. (2011), in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/ep3jh

Probability and randomness are foundational statistical concepts used not only throughout the sciences, but also in our daily lives to guide our behavior and make sense of the world. Their importance and widespread use may suggest that they are easy concepts to understand, yet that seems not to be the case. A classic article by Tversky and Kahneman (1971) on the “belief in the law of small numbers” revealed that professional psychologists tended to incorrectly perceive a small sample that is randomly drawn from a population as representative of that population. This finding has been hugely influential, inspiring myriad subsequent studies into error and bias when reasoning about probability. 

 

In the current study, Hong and Feldman (2023) propose a conceptual replication and extension of Tversky and Kahneman (1971). The original article was shockingly sparse on details regarding the method, sample, and findings, and, to our knowledge, has never been replicated. These facts are especially concerning given the foundational status that the article holds in the field. Hong and Feldman (2023) have developed a conceptual replication project, using the same approach and targeting the same claims from Tversky and Kahneman (1971), but modifying the wording of the stimuli for clarity and appropriateness for lay respondents. Although Tversky and Kahneman (1971) relied on professional psychologists as participants, many of their claims were not restricted to that population, but rather were generalized to all people—which is also how the findings have been subsequently applied. Thus, the change from professional to lay responders is entirely appropriate and the study will be diagnostic of the original claims.

 

Finally, Hong and Feldman (2023) extend the target study by manipulating the sample size indicated in the stimuli. Tversky and Kahneman (1971) relied on a single sample size in each scenario, leaving open the question as to how sample size might impact respondents’ reasoning. Accordingly, Hong and Feldman (2023) vary the sample size across the scenarios to determine whether participants answer differently as the sample size increases. 

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review, the first round consisting of detailed comments from two reviewers and the second round consisting of a close read by the recommender. Based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and was therefore awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/fzbq7
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 

• Advances in Cognitive Psychology
• Experimental Psychology
• F1000Research
• Journal of Cognition
• Meta-Psychology
• Peer Community Journal
• PeerJ
• Royal Society Open Science
• Swiss Psychology Open

 

 

1. Hong, C. K., & Feldman, G. (2023). Revisiting the “Belief in the law of small numbers”: Conceptual replication and extensions Registered Report of problems reviewed in Tversky and Kahneman (1971). In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/fzbq7

 

2. Tversky, A., & Kahneman, D. (1971). Belief in the law of small numbers. Psychological Bulletin, 76(2), 105–110. https://doi.org/10.1037/h0031322   

Emotion is a well-established mediator of decision-making, including prospective economic decisions, but does it affect the way we respond economically to loss? According to classic economic theories, when an object is lost and cannot be recovered, our emotional attachment to that object should be irrelevant for decisions such as choosing whether to claim insurance or compensation. Intriguingly, however, this does not appear to be the case: in a series of experiments, Hsee and Kunreuther (2000) found that when people have higher affection towards an object, they are more sensitive to its loss and are more willing to claim compensation or purchase insurance for the object. They explained these findings according to an influential “consolation hypothesis” in which people see insurance compensation as means to mitigate against the emotional distress associated with property loss.

 

Using a large online sample (N=1000), Law and Feldman (2023) propose to replicate four of six studies from Hsee and Kunreuther (2000), each asking (primarily) whether people with higher affection towards an object are more willing to claim compensation or purchase insurance for that object. In each experiment, participants are randomly assigned to either a high affection group or a low affection group and then given a scenario in which the level of affection to an object is correspondingly manipulated while the monetary value is held constant. For example, for high affection: “You liked the now-damaged painting very much and you fell in love with it at first sight. Although you paid only $100, it was worth a lot more to you”, and for low affection: “You were not particularly crazy about the now-damaged painting. You paid $100 for it, and that’s about how much you think it was worth.” A range of dependent measures are then collected, including the maximum hours participants would be willing to spend driving to claim compensation, the maximum amount participants would be willing to pay for insurance, and how likely participants would be to claim compensation or purchase insurance. As part of the replication, the authors have also built in manipulation checks to confirm that the scenarios influenced participants' (imagined) level of affection for the object, and a range of exploratory analyses.

 

The Stage 1 manuscript was evaluated over two rounds of in-depth review. Based on detailed responses to the reviewers' comments, the recommender judged that the manuscript met the Stage 1 criteria and therefore awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/b7y5z
 
Level of bias control achieved: Level 6. No part of the data or evidence that will be used to answer the research question yet exists and no part will be generated until after IPA.
 
List of eligible PCI RR-friendly journals:
 

 

References
 

1. Hsee, C. K., & Kunreuther, H. C. (2000). The affection effect in insurance decisions. Journal of Risk and Uncertainty, 20, 141-159. https://doi.org/10.1023/A:1007876907268

2. Law, Y. Y. & Feldman, G. (2023). Revisiting the impact of affection on insurance purchase and claim decision-making: Replication and extensions Registered Report of Hsee and Kunreuther (2000), in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/b7y5z

Data sharing is perhaps the most fundamental step for increasing the transparency and reproducibility of scientific research. However, the goals of open science must be tempered by ethical considerations, protecting the privacy and safety of research participants. Bridging this gap causes challenges for many fields, such as human neuroimaging. Brain images, as measured with magnetic resonance imaging (MRI), are unique to the participant and therefore contain identifying information by definition. One way to mitigate the risk to participants arising from public data sharing has been "defacing" the MRI scans, i.e., literally removing the part of the image that contains the face and surrounding tissue, while preserving the brain structure. This procedure however also removes information that is not (or at least minimally) identifiable. It also remains unclear whether defacing the images affects image quality and thus the information necessary for addressing many research questions.

 

The current study by Provins et al. (2023) seeks to address this question. Leveraging a publicly available "IXI dataset" comprising hundreds of T1-weighted structural MRI scans, they will assess the effect of defacing on manual and automatic estimates of image quality. Specifically, the researchers will compare image quality ratings by experts for a subset of 185 images. They hypothesise that images in which facial features have been removed are typically assigned higher quality ratings. Moreover, using a full data set of 580 images, which have been obtained across three scanning sites, they will also test the impact defacing MRI scans has on automated quality measures obtained with MRIQC software. The results of this study should have important implications for open science policy and for designing the optimal procedures for sharing structural MRI data in an ethical way. For example, if the authors' hypothesis is confirmed, studies relying on MRI quality measures might be better served by a custodianship model where identifiable data is shared under strict conditions, rather than relying on publishing defaced data. More generally, the outcome of this study may have significant legal implications in many jurisdictions.

 

The Stage 1 manuscript was evaluated at the inital triage stage by the Recommender and PCI:RR team, and another round of in-depth review by two experts. After a detailed response and substantial revisions, the recommender judged the manuscript met the Stage 1 criteria and awarded in-principle acceptance (IPA).

 

URL to the preregistered Stage 1 protocol: https://osf.io/qcket (under temporary private embargo)
 
Level of bias control achieved: Level 2. At least some data/evidence that will be used to answer the research question has been accessed and partially observed by the authors, but the authors certify that they have not yet observed the key variables within the data that will be used to answer the research question AND they have taken additional steps to maximise bias control and rigour.
 
List of eligible PCI RR-friendly journals:
 

 

1. Provins, C., Savary, E., Alemán-Gómez, Y., Richiardi, J., Poldrack, R. A., Hagmann, P. & Esteban, O. (2023). Defacing biases in manual and automated quality assessments of structural MRI with MRIQC, in principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/qcket