scholarly journals PrePrint Version (Edgcumbe, 2020): The developmental trajectory of open-mindedness: from 18 to 87-years of age.

2020 ◽  
Author(s):  
Daniel Edgcumbe
Keyword(s):  
Decision Making ◽  
Statistical Difference ◽  
Aging Population ◽  
Developmental Trajectory ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Scale Method

Objectives: The present study examined the role of aging in participants between 18 and 87-years of age on open-mindedness in the Actively Open-minded Thinking (AOT) scale and the Actively Open-minded Thinking about Evidence (AOT-E) scale. Method: The amalgamated data from 12 Amazon Mechanical Turk™ studies was analysed. This included a total of 9010 participants (age: M = 37.30, SD = 14.13 / sex: 4191 males, 4734 females and 85 who did not wish to state their sex). All participants completed the 7-item Actively Open-minded Thinking (AOT) scale, of these participants four-hundred and ninety-one also completed the 8-item Actively Open-minded Thinking about Evidence (AOT-E) scale (age: M = 33.27, SD = 5.78 / sex: 2317 males, 2512 females and 62 who did not wish to state their sex). Results: AOT score positively correlated with AOT-E score (r = 0.27). Age negatively correlated with AOT score (r = -0.11) and AOT-E score (r = -0.13). There was a statistical difference in AOT score between the age ranges of participants (18-28, 29-38, 39-48, 49-58, 59-68 and 69-87 years of age). There was also a difference in AOT-E score between the age ranges of participants too. Discussion: The results showed that open-mindedness as measured by the AOT and AOT-E decreased as a function of aging. In an aging population were more adults work into later age the decrease in open-mindedness could influence many areas of judgments of decision-making.

scholarly journals Online Workers

2021 ◽  
pp. 53-66
Author(s):  
Jamie Woodcock
Keyword(s):  
Online Communication ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Digital Networks ◽  
Face To Face ◽  
Labour Process

The focus shifts in this chapter towards online workers. It first differentiates between microworkers and online freelancers, discussing the role of automation and the technical composition of these kinds of work. The chapter contrasts the challenges of organising in this kind of work with transport platforms, particularly the lack of opportunities to meet face-to-face. It draws attention to the digital networks that form around this work in response to the challenges of the labour process. Recent struggles involving Amazon Mechanical Turk and Rev (transcription) workers show the potential for these workers to coordinate and build shared subjectivities through online communication. This case study is explored as an example with a significantly more challenging technical composition, yet shows how new moments of struggle are still coming to the fore.

scholarly journals Fear of Failure and Entrepreneurial Risk Perception

2018 ◽  
Vol 6 (2) ◽  
pp. 45-58
Author(s):  
Nabiha Nefzi
Keyword(s):  
Decision Making ◽  
Risk Perception ◽  
Statistical Difference ◽  
Cognitive Appraisal ◽  
The State ◽  
Fear Of Failure ◽  
Mediating Role ◽  
Entrepreneurial Decision ◽  
The Impact

Abstract The present study provides an understanding of the role of fear of failure in entrepreneurial decision making by examining the mediating role of appraisal dimensions through the study of the impact of fear (state and trait) on entrepreneurial risk perception and using the cognitive-motivational-relational process and the Appraisal Tendencies Framework as based theories. Using a sample of students, we confirmed that trait fear is significantly related with higher entrepreneurial risk perception and this relation is mediated by cognitive appraisal dimensions especially the certainty theme. The same relationship is not confirmed for the state fear, even the statistical difference between students in entrepreneurial risk perception due to state fear condition.

Look Who’s Talking: Mediums of Contact Among Mid-to Later-Life Siblings

2020 ◽  
pp. 009141502091295
Author(s):  
Melanie S. Hill ◽  
Alexander C. Jensen ◽  
Sarah M. Coyne ◽  
Jeremy B. Yorgason
Keyword(s):  
Social Media ◽  
Later Life ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Adult Siblings ◽  
Regression Analyses ◽  
Telephone Contact ◽  
Sibling Closeness

Adult siblings maintain contact and remain close to one another. The current study used participants recruited via Amazon Mechanical Turk ( n = 491) to conduct regression analyses examining five methods of contact (in person, telephone, email, texting, and social media) predicting sibling closeness and conflict. Further, two- and three-way interactions assessed the role of sibling dyad composition (e.g., women with a sister and women with a brother). Results suggested that as contact in person, through social media, the telephone, or email increased, sibling closeness increased, while increased contact through email indicated less conflict. Assessing sibling dyad composition suggested as telephone contact increased, sibling closeness increased for all sibling dyads, especially for women with a sister compared to men with a brother. In-person and texting contacts were beneficial for women with a brother. Even in mid- to later-life, siblings connect through synchronous and asynchronous mediums, and this contact appears beneficial for sisters.

scholarly journals Effect of Prior Gameplay Experience on the Relationships between Esports Gameplay Intention and Live Esports Streaming Content

2021 ◽  
Vol 13 (14) ◽  
pp. 8019
Author(s):  
Wooyoung (William) Jang ◽  
Kevin K. Byon ◽  
Hyunseok Song
Keyword(s):  
Technology Acceptance ◽  
Online Survey ◽  
Prior Experience ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Live Streaming ◽  
Low Frequencies ◽  
Antecedents And Consequences ◽  
And Behavior

This study examined the effect of prior experience with esports gameplay on its antecedents and consequences. Prior experience is considered a significant factor in consumers’ intention and behavior, and in gameplay engagement it is considered the amount of gameplay time. While esports consumers are heterogeneous, only a few esports studies have been conducted. Thus, this study focused on prior esports gameplay experience to explain consumers’ behavior better and examine antecedents, esports gameplay intention, and live esports streaming content across two groups (i.e., high and low frequencies of esports gameplay). Data were collected via an online survey in Amazon Mechanical Turk (M-Turk) from esports consumers who engaged in esports gameplay and live-streaming. One-third of the median cases were excluded to create two groups designated by weekly esports gameplay hours. The results revealed different patterns in the two groups. Specifically, esports gameplay had no effect on engagement in live esports streaming content for consumers who played esport games frequently. However, gameplay intention predicted live esports streaming content engagement successfully in the group who played infrequently. These findings contributed to (1) esports research by demonstrating consumers’ heterogeneity, and the (2) extension of technology acceptance and use research in esports engagement by identifying the role of prior gameplay experience.

scholarly journals Sensitivity to Sunk Costs Depends on Attention to the Delay

2021 ◽  
Vol 12 ◽  
Author(s):  
Rebecca Kazinka ◽  
Angus W. MacDonald ◽  
A. David Redish
Keyword(s):  
Cognitive Processes ◽  
Wait Time ◽  
Sunk Costs ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Wait Times ◽  
Parallel Tasks ◽  
Economic Behaviors

In the WebSurf task, humans forage for videos paying costs in terms of wait times on a time-limited task. A variant of the task in which demands during the wait time were manipulated revealed the role of attention in susceptibility to sunk costs. Consistent with parallel tasks in rodents, previous studies have found that humans (undergraduates measured in lab) preferred shorter delays, but waited longer for more preferred videos, suggesting that they were treating the delays economically. In an Amazon Mechanical Turk (mTurk) sample, we replicated these predicted economic behaviors for a majority of participants. In the lab, participants showed susceptibility to sunk costs in this task, basing their decisions in part on time they have already waited, which we also observed in the subset of the mTurk sample that behaved economically. In another version of the task, we added an attention check to the wait phase of the delay. While that attention check further increased the proportion of subjects with predicted economic behaviors, it also removed the susceptibility to sunk costs. These findings have important implications for understanding how cognitive processes, such as the deployment of attention, are key to driving re-evaluation and susceptibility to sunk costs.

scholarly journals Do group ensemble statistics bias visual working memory for individual items? A registered replication of Brady and Alvarez (2011)

2020 ◽  
Author(s):  
Frank Papenmeier ◽  
J. David Timm
Keyword(s):  
Bayes Factor ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Original Experiment ◽  
Bayesian Evidence ◽  
Memory Representations ◽  
Mean Size ◽  
Factor Design ◽  
Successful Replication

AbstractWe performed a registered and precise replication of Experiment 1 reported in Brady and Alvarez (Psychological Science, 22, 384–392, 2011). The original experiment found that participants, who were asked to memorize the size of differently colored circles, reported the size of a probed circle biased toward the mean size of the same-colored group. Because our previous three unpublished replication attempts failed to find this effect, we powered the present registered replication using a Bayes Factor Design Analysis such that it provided compelling evidence regarding the presence or absence of the reported bias with a high probability, even under the assumption of smaller effect sizes. Thus, we recruited 663 participants through Amazon Mechanical Turk. We observed both a significant bias and strong Bayesian evidence in favor of the existence of a bias over the null hypothesis. Thus, our results can be considered a successful replication of the original findings, although with a considerably smaller effect size. We discuss the role of data quality when recruiting participants with Amazon Mechanical Turk. The present findings corroborate the idea that memory representations of individual objects are influenced by summary statistics.

A Preliminary Exploration of Behaviours Associated with Negative Urgency in Individuals High and Low in Chronic Worry

2021 ◽  
pp. 1-16
Author(s):  
Bailee L. Malivoire ◽  
Kathleen E. Stewart ◽  
Naomi Koerner
Keyword(s):  
Decision Making ◽  
Alcohol Use ◽  
Negative Affect ◽  
Mechanical Turk ◽  
Data Driven ◽  
Amazon Mechanical Turk ◽  
Negative Urgency ◽  
Preliminary Examination ◽  
Data Driven Approach ◽  
Aggressive Behaviours

Abstract While chronic worry is typically associated with cautious and harm-avoidant behaviours, there is evidence that people high in chronic worry are characterised by negative urgency (NU), that is, the propensity to act rashly when experiencing negative affect. The present study was a preliminary examination of how rash action and impulsive decision-making manifest for chronic worriers compared to individuals low in worry. In total, 93 participants who endorsed high and low worry and NU responded to open-ended questions about their experience of NU on Amazon Mechanical Turk. Themes were identified using a data-driven approach. Participants high in chronic worry endorsed significantly greater NU compared to those low in worry. However, the types of NU behaviours were similar across participants, with a majority of responses involving initiating interpersonal conflict. Other themes included spending money, excessive eating, alcohol use, and aggressive behaviours. The manifestations of NU were largely consistent with those described in the model of NU. Although individuals higher in chronic worry engaged in NU behaviours to a greater extent, the types of behaviours were similar to those reported by people lower in worry. More research is needed to understand the characteristics of NU-motivated behaviour in individuals high in chronic worry.

scholarly journals Signaling when no one is watching: A reputation heuristics account of outrage and punishment in one-shot anonymous interactions

2019 ◽  
Author(s):  
Jillian Jordan ◽  
David Gertler Rand
Keyword(s):  
Individual Differences ◽  
Third Party ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Moral Outrage ◽  
Total N ◽  
Mediation Analyses ◽  
Costly Punishment ◽  
Using Data

Moralistic punishment can confer reputation benefits by signaling trustworthiness to observers. But why do people punish even when nobody is watching? We argue that people often rely on the heuristic that reputation is typically at stake, such that reputation concerns can shape moral outrage and punishment even in one-shot anonymous interactions. We then support this account using data from Amazon Mechanical Turk. In anonymous experiments, subjects (total n = 8440) report more outrage in response to others’ selfishness when they cannot signal their trustworthiness through direct prosociality (sharing with a third party)—such that if the interaction were not anonymous, punishment would have greater signaling value. Furthermore, mediation analyses suggest that sharing opportunities reduce outrage by decreasing reputation concerns. Additionally, anonymous experiments measuring costly punishment (total n = 6076) show the same pattern: subjects punish more when sharing is not possible. And importantly, moderation analyses provide some evidence that sharing opportunities do not merely reduce outrage and punishment by inducing empathy towards selfishness or hypocrisy aversion among non-sharers. Finally, we support the specific role of heuristics by investigating individual differences in deliberateness. Less deliberative individuals (who typically rely more on heuristics) are more sensitive to sharing opportunities in our anonymous punishment experiments, but, critically, not in punishment experiments where reputation is at stake (total n = 3422); and not in our anonymous outrage experiments (where condemning is costless). Together, our results suggest that when nobody is watching, reputation cues nonetheless can shape outrage and—among individuals who rely on heuristics—costly punishment.

scholarly journals Who Doesn’t Want to Share Leadership? The Role of Personality, Control Preferences, and Political Orientation in Preferences for Shared vs. Focused Leadership in Teams

2019 ◽  
pp. 11-27
Author(s):  
Anna Olga Kuzminska ◽  
◽  
Dominic Schulze ◽  
Anna Koval ◽  
◽  
...  
Keyword(s):  
Personality Traits ◽  
Distributed Leadership ◽  
Shared Leadership ◽  
Well Being ◽  
Political Orientation ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Equal Division ◽  
Leadership Model

An increasing number of institutions decide to adopt the premises of shared or distributed leadership models and reduce the level of organizational hierarchy. Such models were shown to positively affect employee well-being, creativity, and – indirectly – effectiveness. However, while shared leadership assumes a relatively equal division of control in interdependent situations, some people display preferences to dominate or submit. What is more, unequal/equal division of power may be preferable to people with a more conservative/liberal political orientation. In the current research we examine whether the shared leadership model is likely to be equally attractive to all employees. We focus on the effect of personality traits, control preferences, and political orientation on preferences for shared vs. focused leadership. One-hundred-and-eighty-four participants declared their team preferences (focused vs. shared leadership), as well as answered questions regarding their personality (HEXACO), control preferences, and political orientation through the Amazon Mechanical Turk platform. Control preferences, as well as political orientation were related to preferences for shared vs. focused leadership. Specifically, while dominance and conservative political orientation was associated with higher preference for focused leadership, collaboration predicted higher preference for shared leadership. Personality traits did not predict the preferences for focused vs. shared leadership

scholarly journals A systematic investigation of differences in perceptual decision-making as a function of the time and method of participant recruitment

2020 ◽  
Author(s):  
Timothy Ballard ◽  
Gina Fisher ◽  
David K. Sewell
Keyword(s):  
Decision Making ◽  
Discrimination Task ◽  
Standard Stimulus ◽  
Brightness Discrimination ◽  
Discrimination Performance ◽  
Mechanical Turk ◽  
Amazon Mechanical Turk ◽  
Perceptual Decision Making ◽  
Perceptual Decision ◽  
Speed Accuracy

We examine the extent to which perceptual decision-making processes differ as a function of the time in the academic term in which the participant enrolls in the experiment and whether the participant is an undergraduate who completes the experiment for course credit, a paid participant who completes the experiment in the lab, or a paid participant recruited via Amazon Mechanical Turk who completes the experiment online. In Study 1, we conducted a survey to examine cognitive psychologists' expectations regarding the quality of data obtained from these different groups of participants. We find that cognitive psychologists expect performance and response caution to be lowest among undergraduate participants who enroll at the end of the academic term, and highest among paid in-lab participants. Studies 2 and 3 tested these expectations using two common perceptual decision-making paradigms. Overall, we found little evidence for systematic time-of-term effects among undergraduate participants. The different participant groups responded to standard stimulus quality and speed/accuracy emphasis manipulations in similar ways. Among participants recruited via Mechanical Turk, the effect of speed/accuracy emphasis on response caution was strongest. This group also showed poorer discrimination performance than the other groups in a motion discrimination task, but not in a brightness discrimination task. We conclude that online crowdsourcing platforms can provide high quality perceptual decision-making data, but give recommendations for how data quality can be maximized when using these platforms for recruitment.

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