Studying eye-gaze has long been employed as a central method for understanding attentional dynamics and cognitive processes in a variety of domains. The development of affordable, mobile eye-tracking devices, such as the Pupil Neon, promises new opportunities to extend this research beyond the contexts in which traditional eye-trackers have been available. But how good are such novel devices at detecting variables relevant for the study of eye movements and pupil dilations?

 

Foucher, Krug and Sauter (2024) propose an independent evaluation of the Pupil Neon eye-tracker using the Ehinger et al. (2019) test battery, comparing its performance with a traditional EyeLink 1000 Plus device. In an empirical study, participants will be asked to perform a wide variety of tasks while eye movements and pupil dilations are tracked using both devices. Results on the strengths and weaknesses, as well as potential use cases of the Pupil Neon will be informative for subsequent eye-tracking research. 

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

 

 

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. 

 

 

1. Ehinger, B. V., Groß, K., Ibs, I., and König, P. (2019). A New Comprehensive Eye-Tracking Test Battery Concurrently Evaluating the Pupil Labs Glasses and the Eyelink 1000. PeerJ, 7, e7086. https://doi.org/10.7717/peerj.7086

2. Foucher, V., Krug, A., and Sauter, M. (2024). Independent Comparative Evaluation of the Pupil Neon - A New Mobile Eye-tracker. In principle acceptance of Version 3 by Peer Community in Registered Reports. https://osf.io/3kc5t

 

Revisiting a true classic, this registered replication report addresses Kahneman and Tversky’s (1973) introduction of the representativeness heuristic. The heuristic refers to deviations of judgments from normative evaluations of the evidence when the stimulus fits to a prototype. For instance, when an individual is described by features stereotypically associated with a certain target group (e.g., a person who attends dance training several times a week and has a passion for singing and performing), likelihood judgments that the individual belongs to a target group (K-Pop artists) compared to a non-target group (e.g., accountants) are inflated. 

The impact of the original research on the field is clearly immense and long-lasting. All the better that a systematic replication attempt is being undertaken in this registered report, which addresses studies 1 through 7 of Kahneman and Tversky’s classic 1973 paper. Chan and Feldman (2024) propose a well-powered online study, in which all studies from the original article are presented to participants within-subjects. The materials are carefully constructed and closely documented in the accompanying OSF project, where in-depth information on planned data analyses is supported with a simulated dataset.  

The Stage 1 manuscript was evaluated over three 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).

 

 

Level of bias control achieved: Level 6. Data collection commenced during the later part of Stage 1 peer review; however, since no substantive changes to the design were made after this point, the risk of bias due to prior data observation remains zero and the manuscript therefore qualifies for Level 6.

 

 

 

1. Chan, H. C. & Feldman, G. (2024). Representativeness heuristic in intuitive predictions: Replication Registered Report of problems reviewed in Kahneman and Tversky (1973). In principle acceptance of Version 5 by Peer Community in Registered Reports. https://osf.io/er2cq

 

2. Kahneman, D., & Tversky, A. (1973). On the psychology of prediction. Psychological Review, 80(4), 237–251. https://doi.org/10.1037/h0034747

 

The Martyrdom Effect is a behavioral tendency in which individuals exhibit greater generosity when their acts of giving entail effort or self-sacrifice (Olivola & Shafir, 2013). Giving at a personal cost, in this mindset, is associated with ascribing and inferring more meaning and value to charitable giving or other forms of generosity than in instances where no particular pain or effort is required to enact prosocial behavior. Arguably, the Martyrdom Effect’s ability to boost prosocial behavior therefore departs from other theories of behavior change postulating that easy options to act prosocially could boost contributions (e.g., default effects in charitable giving, see Altmann et al., 2019; Goswami & Urminsky, 2016). Because they introduce complexity to the debate about encouraging prosocial behavior, three studies from Olivola and Shafir (2013) are now being addressed in this Registered Report by Cheng and Feldman (2024).

Combining these three studies in a high-powered within-subjects replication attempt, transparently communicating necessary deviations from the original design and carefully outlining the analysis strategy, the current study will offer insights into the robustness of prior findings on the role of effort and pain in determining donations.

The Stage 1 manuscript was evaluated by two reviewers and the recommender. 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).

 

 

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. Altmann, S., Falk, A., Heidhues, P., Jayaraman, R., & Teirlinck, M. (2019). Defaults and Donations: Evidence from a Field Experiment. The Review of Economics and Statistics, 101, 808-826. https://doi.org/10.1162/rest_a_00774

 

2. Cheng, Y. T. & Feldman, G. (2024). Do pain and effort increase prosocial contributions?: Revisiting the Martyrdom Effect with a Replication and extensions Registered Report of Olivola and Shafir (2013). In principle acceptance of Version 2 by Peer Community in Registered Reports. https://osf.io/aq89u

 

3. Goswami, I., & Urminsky, O. (2016). When should the Ask be a Nudge? The Effect of Default Amounts on Charitable Donations. Journal of Marketing Research, 53, 829-846. https://doi.org/10.1509/jmr.15.0001

 

4. Olivola, C. Y., & Shafir, E. (2013). The Martyrdom Effect: When Pain and Effort Increase Prosocial Contributions. Journal of Behavioral Decision Making, 26, 91-105. https://doi.org/10.1002/bdm.767

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