Friday, May 14, 2021

The Cross-national Association of Gun Ownership Rates and Suicide Rates: An Analysis of 194 Nations

The Cross-national Association of Gun Ownership Rates and Suicide Rates: An Analysis of 194 Nations. Gary Kleck. Archives of Suicide Research, May 12 2021.


Objective: To estimate the cross-national association between suicide rates and gun ownership rates

Method: The association is estimated using the largest sample of nations (n = 194) ever employed for this purpose. Three different measures of national gun ownership rates are related to total suicide rates, firearms suicide rates, and non-firearms suicide rates.

Results: Although gun ownership rates have a significant positive association with the rate of firearms suicide, they are unrelated to the total suicide rate.

Conclusions: Consistent with the results of most prior macro-level studies, cross-national data indicate that levels of gun availability appear to affect how many people choose shooting as their method of suicide, but do not affect how many people kill themselves.

Keywords: Cross-nationalgun ownershipsuicide rates

Interventions to induce skepticism had a significantly stronger average effect on attitudes than did ones that intended to promote belief in climate change; seems that belief in climate change is more easily weakened than strengthened

Influencing Climate Change Attitudes in the United States: A Systematic Review and Meta-Analysis. Jacob B.Rode, Amy L.Dent, Caitlin N.Benedict, Daniel B.Brosnahan, Ramona L.Martinez, Peter H.Ditto. Journal of Environmental Psychology, May 14 2021, 101623.


• A meta-analysis was conducted on interventions for climate change attitudes.

• There was a small, statistically significant positive effect of interventions.

• Interventions were less effective at influencing policy attitudes than belief.

• There was no intervention type that was clearly the most effective.

Abstract: Researchers interested in climate change communication have investigated how people respond to messages about it. Through meta-analysis, the current research synthesizes the multitude of experimental studies on this topic to uncover which interventions are most effective at influencing attitudes about climate change. The meta-analysis focuses on experimental studies that included a control condition and measured climate change attitudes among participants in the United States. After a large literature search, 396 effect sizes were retrieved from 76 independent experiments (N = 76,033 participants). Intervention had a small, significant positive effect on attitudes, g = 0.08, 95% CI [0.05, 0.10], 95% prediction interval [-0.04, 0.19], p < .001. Surprisingly, type of intervention was not a statistically significant moderator of this effect, nor was political affiliation. However, type of attitude was a significant moderator: the treatment-control difference in attitudes was smaller for policy support than for belief in climate change, indicating that policy attitudes are more resistant to influence than belief in climate change. Interventions that aimed to induce skepticism (e.g., misinformation) had a significantly stronger average effect on attitudes than did ones that intended to promote belief in climate change, suggesting that belief in climate change is more easily weakened than strengthened.

Keywords: climate changeattitudesmeta-analysisinterventions

The Political Consequences of an Optimistic Personality: Is a psychological resource that contributes to the practice of good citizenship behaviors (more politically engaged & participatory than those with pessimistic dispositions)

The Political Consequences of an Optimistic Personality. Carey Stapleton, Jacob Oliver & Jennifer Wolak. Political Behavior, May 13 2021.

Abstract: Optimists hope for the best possible outcome, while pessimists plan for the worst. We investigate how people’s predispositions to be optimistic versus pessimistic shape how they approach politics. We argue that an optimistic personality is a psychological resource that contributes to the practice of good citizenship behaviors. Using responses from the 2008 Cooperative Campaign Analysis Project and the 2018 Cooperative Congressional Election Study, we demonstrate that people with optimistic personalities are more politically engaged and participatory than those with pessimistic dispositions. Optimists express more positive views of the American people, the government, and national symbols as well. Because optimists have a more positive outlook toward the nation’s future, they help contribute to levels of diffuse support for government and its symbols. While we might worry that optimists hold an unrealistic view of the political world, we find little evidence that dispositional optimism is associated with less accurate perceptions of political realities.

From 2019... Personal info than can be inferred from eye-tracking data: A user's sex, age, ethnicity, personality traits, drug-consumption habits, emotions, fears, skills, interests, sexual preferences, & physical & mental health

From 2019... Kröger J.L., Lutz O.HM., Müller F. (2020) What Does Your Gaze Reveal About You? On the Privacy Implications of Eye Tracking. In: Friedewald M., Önen M., Lievens E., Krenn S., Fricker S. (eds) Privacy and Identity Management. Data for Better Living: AI and Privacy. Privacy and Identity 2019. IFIP Advances in Information and Communication Technology, vol 576. Springer, Cham. March 2020.

Abstract: Technologies to measure gaze direction and pupil reactivity have become efficient, cheap, and compact and are finding increasing use in many fields, including gaming, marketing, driver safety, military, and healthcare. Besides offering numerous useful applications, the rapidly expanding technology raises serious privacy concerns. Through the lens of advanced data analytics, gaze patterns can reveal much more information than a user wishes and expects to give away. Drawing from a broad range of scientific disciplines, this paper provides a structured overview of personal data that can be inferred from recorded eye activities. Our analysis of the literature shows that eye tracking data may implicitly contain information about a user’s biometric identity, gender, age, ethnicity, body weight, personality traits, drug consumption habits, emotional state, skills and abilities, fears, interests, and sexual preferences. Certain eye tracking measures may even reveal specific cognitive processes and can be used to diagnose various physical and mental health conditions. By portraying the richness and sensitivity of gaze data, this paper provides an important basis for consumer education, privacy impact assessments, and further research into the societal implications of eye tracking.

Keywords: Eye tracking Gaze Pupil Iris Vision Privacy Data mining Inference 

3 Discussion and Implications

As shown in the previous section, various kinds of sensitive inferences can be drawn from eye tracking data. Among other categories of personal data, recorded visual behavior can implicitly contain information about a person’s biometric identity, personality traits, ethnic background, age, gender, emotions, fears, preferences, skills and abilities, drug habits, levels of sleepiness and intoxication, and physical and mental health condition.  To some extent, even distinct stages of cognitive information processing are discernable from gaze data. Thus, devices with eye tracking capability have the potential to implicitly capture much more information than a user wishes and expects to reveal. Some of the categories of personal information listed above constitute special category data, for which particular protection is prescribed by the EU’s General Data Protection Regulation (Art. 9 GDPR).  Of course, drawing reliable inferences from eye tracking data is not a trivial task.

Many situational factors can influence eye properties and gaze behavior in complex ways, making it difficult to measure the effect of a particular action, internal process, or personal characteristic of the user in isolation [55]. Seemingly identical ocular reactions can result from completely different causes. For example, an intensive gaze fixation on another person’s face may indicate liking, aversion, confusion, recognition, and much more. Similarly, a sudden change in pupil size can be indicative of many different feelings or internal states, including physical pain, sexual arousal, interest, happiness, anger, or simply be a reaction to ambient events and conditions, such as noise or varying lighting [19, 55].

In spite of existing challenges and limitations, the reviewed literature demonstrates that there is considerable potential for inferences in many areas and that numerous research projects, patented systems, and even commercial products have already taken advantage of the richness of eye tracking data to draw inferences about individuals with high accuracy.

It should be acknowledged that many of the cited inference methods were only tested under controlled laboratory conditions and lack evaluation in real-world scenarios [4, 18, 27, 52, 65, 67, 69, 86, 88]. On the other hand, it may reasonably be assumed that some of the companies with access to eye tracking data from consumer devices (e.g., device manufacturers, ecosystem providers) possess larger sets of training data, more technical expertise, and more financial resources than the researchers cited in this paper.  Facebook, for example, a pioneer in virtual reality and eye tracking technology, is also one of the wealthiest and most profitable companies in the world with a multi-billion dollar budget for research and development and a user base of over 2.3 billion people [93]. It seems probable that the threat of unintended information disclosure from gaze data will continue to grow with further improvements of eye tracking technology in terms of cost, size, and accuracy, further advances in analytical approaches, and the increasing use of eye tracking in various aspects of daily life.

In assessing the privacy implications of eye tracking, it is important to understand that, while consciously directed eye movements are possible, many aspects of ocular behavior are not under volitional control – especially not at the micro level [19, 55].  For instance, stimulus-driven glances, pupil dilation, ocular tremor, and spontaneous blinks mostly occur without conscious effort, similar to digestion and breathing. And even for those eye activities where volitional control is possible, maintaining it can quickly become physically and cognitively tiring [58] – and may also produce certain visible patterns by which such efforts can be detected. Hence, it can be very difficult or even impossible for eye tracking users to consciously prevent the leakage of personal information.

Though this paper focuses on privacy risks, we do not dispute the wide-ranging benefits of eye tracking. Quite the opposite: we believe that it is precisely the richness of gaze data and the possibility to draw insightful inferences from it that make the rising technology so valuable and useful. But to exploit this potential in a sustainable and socially acceptable manner, adequate privacy protection measures are needed.

Technical safeguards have been proposed to prevent the unintended disclosure of personal information in data mining, including specialized solutions for eye tracking data [58, 80]. These comprise the fuzzing of gaze data (i.e., inserting random noise into the signal before passing it down the application chain) and the utilization of derived parameters (e.g., aggregated values instead of detailed eye fixation sequences) [58]. Experiments have already shown that approaches based on differential privacy can prevent certain inferences, such as user re-identification and gender recognition, while maintaining high performance in gaze-based applications [80]. In addition to approaches at the technical level, it should also be examined whether existing laws provide for sufficient transparency in the processing of gaze data and for proper protection against inference-based privacy breaches. The promises and limitations of existing technical and legal remedies are beyond the scope of this paper but deserve careful scrutiny and will be considered for future work.

Even though eye tracking is a demonstrative example, the threat of undesired inferences is of course much broader, encompassing countless other sensors and data sources in modern life [47]. In other recent work, we have examined sensitive inferences that can be drawn from voice recordings [49] and accelerometer data [48, 50], for instance. In our view, the vast possibilities of continuously advancing inference methods are clearly beyond the understanding of the ordinary consumer. Therefore, we consider it to be primarily the responsibility of technical experts, technology companies, and governmental agencies to inform consumers about potential consequences and protect them against such covert invasions of privacy. Also, since it is unlikely that companies will voluntarily refrain from using or selling personal information that can be extracted from already collected data, there should be strong regulatory incentives and controls

About the economy, women are less likely to provide a judgment than their male counterparts, are less likely to give "extreme" answers in which they strongly agree or disagree, & are less confident in their answer's accuracy

Confidence Men? Evidence on Confidence and Gender among Top Economists. Heather Sarsons and Guo Xu. AEA Papers and Proceedings. May 2021, Vol. 111, No. : Pages 65-68.

Abstract: Using data from economists working in top US universities, we find that women are less confident than men along three margins. When asked about their level of agreement on survey questions about the economy, women are less likely to provide a judgment than their male counterparts. Conditional on providing a judgment, women are less likely to give "extreme" answers in which they strongly agree or disagree. Women are also less confident in the accuracy of their answer. We show that the confidence gap is driven by women being less confident when asked questions outside their field of expertise.


Women are 7.3 percentage points less likely to provide extreme judgments (column 1). In terms of magnitude, this gap is economically large. Compared to the mean of the dependent vari-able (19.8 percent), this corresponds to a gap of 36 percent. The gap is somewhat smaller for the self-reported confidence level but still nontrivial (column 3). On average, women tend to report a confidence score that is 0.221 points lower than men. This corresponds to a gap of 4 percent when evaluated against the mean...

The results show that both men and women are less confident when asked questions outside of their field but that a confidence gap persists. For example, while men are 5 percentage points less likely to give an extreme answer when speaking on a topic out-side of their primary field, women are 9.2 per-centage points less likely to do so (column 1). For the measure of confidence, men are on aver-age 0.585 points less confident when speaking on a topic outside their primary field (column 2). Once again, that confidence gap is significantly larger for women. We would expect women to be less confident than men when answering questions outside of their field if women actually have a narrower range of expertise than men do. The results, however, do not change when we control for the respondents’ breadth of expertise using RePEc data and allow breadth to vary by gender. More importantly, accounting for the differential confidence when moving beyond one’s own field “explains away” the level effect of gender.

[...] it appears that the confidence gap emerges when women are speaking on topics on which they might be less informed.