Permanently Online—Always Stressed Out? The Effects of Permanent Connectedness on Stress Experiences

Permanently Online—Always Stressed Out? The Effects of Permanent Connectedness on Stress Experiences. Anna Freytag, Katharina Knop-Huelss, Adrian Meier, Leonard Reinecke, Dorothée Hefner, Christoph Klimmt, Peter Vorderer. Human Communication Research, hqaa014, December 30 2020. https://doi.org/10.1093/hcr/hqaa014

Abstract: Concerns have been expressed that permanent online connectedness might negatively affect media user’s stress levels. Most research has focused on negative effects of specific media usage patterns, such as media multitasking or communication load. In contrast, users’ cognitive orientation toward online content and communication has rarely been investigated. Against this backdrop, we examined whether this cognitive orientation (i.e., online vigilance with its three dimensions salience, reactibility, monitoring) is related to perceived stress at different timescales (person, day, and situation level), while accounting for the effects of multitasking and communication load. Results across three studies showed that, in addition to multitasking (but not communication load), especially the cognitive salience of online communication is positively related to stress. Our findings are discussed regarding mental health implications and the origins of stress.

Unfamiliar faces look sicker; familiar ones look healthier; and during a pandemic the ramifications of neither proposition look good

Strangers look sicker (with implications in times of COVID‐19). Paola Bressan. BioEssays, November 20 2020. https://doi.org/10.1002/bies.202000158

Rolf Degen's take: https://twitter.com/DegenRolf/status/1345432495551107072

Abstract: We animals have evolved a variety of mechanisms to avoid conspecifics who might be infected. It is currently unclear whether and why this “behavioral immune system” targets unfamiliar individuals more than familiar ones. Here I answer this question in humans, using publicly available data of a recent study on 1969 participants from India and 1615 from the USA. The apparent health of a male stranger, as estimated from his face, and the comfort with contact with him were a direct function of his similarity to the men in the local community. This held true regardless of whether the face carried overt signs of infection. I conclude that our behavioral immune system is finely tuned to degrees of outgroupness — and that cues of outgroupness are partly processed as cues of infectiousness. These findings, which were consistent across the two cultures, support the notion that the pathogens of strangers are perceived as more dangerous.

Box 1: Why Nonlocal Pathogens Spell More Danger

The findings I report here endorse the principle (nonlocal parasites are treated as though they were more dangerous) but not necessarily the underlying mechanism — coevolution between host populations and their parasites — as originally outlined by Fincher and Thornhill.[19] For example, it has been objected[28] that coevolution might often work in a direction contrary to that presupposed by the theory. Many pathogens are selected to spread best, or do most damage, within their current host population (i.e., to be “locally adapted”;[29] but see[30]) and would cause less, rather than more, trouble in neighboring groups. True, contact between separate groups has led to disastrous epidemics,[20] but such occurrences would have been rare and only relevant to totally isolated populations, rather than to the adjoining communities typical of our evolutionary history.[28] Yet the unfamiliar‐pathogens theory could work even if coevolution entered the picture only occasionally or not at all. We may prove more vulnerable to outgroup parasites not because these are more virulent due to our maladaptation to them, but simply because numerous illnesses leave us with immune cells that respond efficiently to subsequent exposure to the same pathogens as opposed to novel ones (see also[20, 28]). It is indeed telling that, in many species, exposure to new parasites is meticulously regulated. For example, several primates keep a newcomer at the periphery of the group for weeks or months before allowing it in. This admission practice not only makes it likely that any latent infection will reveal itself, but also ensures lengthy low‐level exposure to the alien pathogens — permitting residents to develop immunity to them before the stranger carries them into the group in large numbers.[24, 25]

IT'S A SMALL WORLD

Unfamiliar faces look sicker; familiar ones look healthier; and during a pandemic the ramifications of neither proposition look good. In times of COVID‐19, the only comforting thing that can be said of these findings’ implications is that they are scientifically very interesting. The sicker our fellow humans appear, the more we feel compelled to keep them out of the way — which we do also by becoming unkind, prejudiced, intolerant, and aggressive. There is no escaping the pressure of an infection threat as formidable as COVID‐19 on millions of behavioral immune systems, to the effect that our prospects for world peace and universal harmony are unlikely to take an upturn anytime soon.

Yet the other side of the coin — familiar faces seem healthier — is hardly a compensation when the pathogen we are up against is entirely novel. In unremarkable times the special intimacy we enjoy with our ingroup serves us quite nicely, because we are better adapted to their parasites than to the outgroup's. No human, however, is pre‐adapted to viruses that jump out overnight from bats or camels or pangolins[56] and quickly proceed to invade a globalized and hyperconnected world. Being ingroup or outgroup matters no longer: but not in the sense that one would have hoped for. And of course our ingroup‐loving instincts continue to run as blindly as they always have done. Impressively, comfort with contact with familiar‐looking individuals was higher than the neutral point even in front of a glaring contagion cue (infected ingroup: left panel of Figure 2, rightmost solid symbols). That is, provided they look like community members, unmistakably infectious strangers appear fine to shake hands with and sit close to; strict proximity to them feels more comfortable than uncomfortable. It is not a matter of contagiousness being misconstrued either, because the very same signs keep us well away from those who look different from the locals (infected outgroup: left panel of Figure 2, leftmost solid symbols). With a pandemic ongoing — let alone one that presents with a lack of obvious symptoms[57] rather than with a disgusting facial rash — these findings are disquieting.

The behavioral response of individuals to an epidemic is capable of altering its dynamics with catastrophic consequences.[58, 59] The most effective measure to stop or slow down the spread of airborne diseases like COVID‐19 is to avoid person‐to‐person proximity (in conjunction with wearing masks whenever spatial or temporal separation is less than ideal,[60] which in places shared with others means virtually always[61, 62]). In the face of infection, social distancing is practiced in nature by mostly every species except superlatively social ones, such as bats[63] and mongooses,[64] where group members are connected so tightly that isolation might prove undesirable, and pathogen exposure is inevitable. Of course, spontaneous social distancing is driven by the detection of physical or behavioral signs of infection, which in humans is largely unconscious[5] and not necessarily accurate. For example, we are unable to judge from the sound alone whether a cough comes from someone who is infected or not; disgusting coughs appear more alarming regardless.[65] Here I have shown that identical infection cues can be perceived as more or less threatening, and lead to a stronger or weaker avoidance response, depending on whether they show up on unfamiliar or familiar faces. A weaker avoidance response translates, needless to say, into reduced spontaneous social distancing and reduced compliance with enforced social distancing.

Mathematical models of human epidemics have begun to recognize that not everyone in a population has an equal chance to become infected or infect others. Infections propagate primarily through networks that, being formed by individuals who are habitually in contact, tend to be clustered in space.[66] Yet, unless one is modelling the inhabitants of North Sentinel Island, there also exist rare random links to distant individuals (“small‐world” networks[67]), which permit infection to expand relatively quickly — allowing indeed for multiple epidemics or even pandemics. The findings I have presented hold two implications for disease transmission. First, individuals are more likely to infect and be infected by community members, as opposed to nonmembers, not only because they meet them more often and for a longer time;[68] but also because — on account of perceiving them as healthier and hence safer — they are bound to take fewer precautions upon meeting them. And second, individuals are more likely to infect, and be infected by, strangers who are not even community members but just look similar to them. This bears evident potential repercussions on contagion patterns: predicting as it does, for instance, that at the start of the COVID‐19 outbreak in the USA white Americans might have been less guarded toward (possibly infected) white European tourists than toward healthy fellow Americans of African origin. Thus, perceived familiarity effectively reduces the distance between individuals within a network, changing their probability of both acquiring and transmitting infection. Incorporating properties such as familiarity or outgroupness to alter the weight of the links between individuals may increase models’ realism, with immediate relevance to epidemiology.

I have proposed that facial familiarity decreases infection cues’ perceived threat by serving as a proxy for previous exposure to the same pathogens. Mandrills abstain from grooming contagious mates unless these are close maternal kin (mother, offspring, maternal half‐siblings) and it has been suggested they might be less sensitive to infection cues associated with kin.[69] Note, however, that they treat infected paternal half‐siblings exactly as they treat infected distant kin or nonkin, even though paternal half‐siblings are every bit as related to them as are maternal ones, and can be recognized as kin.[70] Yet of course maternal half‐siblings are exposed to one another a great deal because they are raised together from birth, whilst paternal half‐siblings grow up in entirely different families.[70] I suggest, then, that mandrills’ disregard of contagion when attending to maternal kin might reflect not their genetic relationship, but their larger familiarity with them and hence with their parasites.

CONCLUSIONS: TO THE BEHAVIORAL IMMUNE SYSTEM ALL STRANGERS ARE EQUAL, BUT SOME STRANGERS ARE MORE EQUAL THAN OTHERS

The results described in this paper fit effortlessly what I have called the “unfamiliar‐pathogens” theory — a facet of the general parasite‐stress explanation of human behavior ([19, 53]; see also[16]). Building upon new data, here I have unpacked the basic idea and stretched it slightly in depth and breadth. I have argued that our treacherous cohabitation with parasites has forced on us the compulsion to assess others’ dissimilarity from the people to whom we are usually exposed (our quintessential “ingroup”). Individuals who do not look like them are likely to be coming from elsewhere, carrying pathogens that are novel to us and thus more dangerous. Therefore, our behavioral immune system has specifically evolved to pay “outgroups” the greatest attention, perceiving them as sicker from the start. And because the members of our local, familiar community embody “normality,” and outgroupness is detected as a deviation from that, our aversion generalizes to all deviations from normality. This can only deepen and widen our disinclination to engage with people who are (or we perceive as) malformed, disfigured, disabled, or just “strange” — anomalies that happen to be statistically associated to disease on their own merits.

If the idea laid out here is correct, discomfort with contact should not be confined to actual strangers or atypical individuals but extend to familiar, ordinary‐looking community members we seldom bump into. Indeed, when 30,000 people from 165 countries were asked who was the least likely person they would share a toothbrush with, 2% indicated their spouse, 25% the boss at work, and 60% the postman.[71] Our spouses, bosses, and postmen do not represent increasing degrees of outgroupness in terms of which tribe or village or ethnicity they belong to. They do, however, in terms of how regularly they happen to lavish their own parasites on us.

Negativity Spreads More Than Positivity on Twitter After Both Positive and Negative Political Situations

Schöne, Jonas, Brian Parkinson, and Amit Goldenberg. 2021. “Negativity Spreads More Than Positivity on Twitter After Both Positive and Negative Political Situations.” PsyArXiv. January 2. doi:10.31234/osf.io/x9e7u

Abstract: What type of emotional language spreads further in political discourses on social media? Previous research has focused on situations that primarily elicited negative emotions, showing that negative language tended to spread further. The current project addressed the gap introduced when looking only at negative situations by comparing the spread of emotional language in response to both predominantly positive and negative political situations. In Study 1, we examined the spread of emotional language among tweets related to the winning and losing parties in the 2016 US elections, finding that increased negativity (but not positivity) predicted content sharing in both situations. In Study 2, we compared the spread of emotional language in two separate situations: the celebration of the US Supreme Court approval of same-sex marriage (positive), and the Ferguson Unrest (negative), finding again that negativity spread further. These results shed light on the nature of political discourse and engagement.

Check also COVID-19: 91pct of stories by US major media outlets are negative in tone vs 65pct for scientific journals; stories of increasing cases are 5.5x stories of decreasing cases even when new cases are declining

Why Is All COVID-19 News Bad News? Sacerdote, Bruce and Sehgal, Ranjan and Cook, Molly. National Bureau of Economic Research, Working Paper 28110, Nov 2020. https://www.bipartisanalliance.com/2020/11/covid-19-91pct-of-stories-by-us-major.html

Sweden: Women in this work were more likely than men to avoid eating gluten, red meat, white flour and food additives due to perceived unhealthiness, and reported more diet and health related anxiety

Gender differences in perceived food healthiness and food avoidance in a Swedish population-based survey: a cross sectional study. Linnea Bärebring, Maria Palmqvist, Anna Winkvist & Hanna Augustin. Nutrition Journal volume 19, Article number: 140, Dec 29 2020. https://link.springer.com/article/10.1186/s12937-020-00659-0

Rolf Degen's take: https://twitter.com/DegenRolf/status/1345253441212477440

Abstract

Background: The aim of this work was to study potential gender differences in perceived food healthiness and food avoidance in a population-representative sample of the Swedish adult population.

Methods: A questionnaire regarding diet and health was posted to 2000 randomly selected residents in Sweden, aged 20–65 years. Questions were posed regarding which foods or food components the participants avoided due to perceived unhealthiness and how healthy they believed the food items to be. The pre-specified food components included sugar, carbohydrate, gluten, lactose, dairy, fat, saturated fat, red meat, white flour, salt, alcohol and food additives (specifically glutamate, sweetening, preservative and coloring agents). Chi square tests were used to study differences in perceived food healthiness and food avoidance depending on gender.

Results: Around 50% reported avoidance of sugar (51.6%) and sweeting agents (45.2%), whereas fewer reported avoidance of saturated fat (16.8%) and salt (10.6%). Women were more likely than men to avoid gluten (AOR [95% CI] 2.84 [1.33–6.05]), red meat (3.29 [1.86–5.80]), white flour (2.64 [1.65–4.21]), preservatives (1.7 [1.07–2.70]) and coloring agents (2.10 [1.29–3.41]) due to perceived unhealthiness. Gender differences were also apparent in perceived healthiness of sugar, gluten, dairy, red meat, white flour, alcohol and food additives, where women tended to be more negative than men in their attitudes. Women more often said to read new findings in media about diet (16% vs 9%, p = 0.029) and prioritize a healthy lifestyle (35% vs 25%, p = 0.015). More than a third of both women and men reported worrying over the healthiness of their diet, and a higher proportion of women than men (18% vs 11%, p = 0.015) agreed with the statement that they were often anxious over having an unhealthy diet.

Conclusions: Women in this population-based study of residents in Sweden were more likely than men to avoid eating gluten, red meat, white flour and food additives due to perceived unhealthiness, and reported more diet and health related anxiety. Future research to identify effective ways of promoting healthy eating for both women and men, while minimizing diet-health related anxiety, is highly warranted.

Discussion

The results of this study show that there are gender differences in both perceived food healthiness and in food avoidance in Sweden. Overall, women reported more negative perceptions on the healthiness of sugar, gluten, dairy, red meat, white flour, alcohol and food additives. In addition, women were more likely to avoid gluten, red meat, white flour and food additives. Women also reported more anxiety related to food and health.

We found that there are gender differences in perceived healthiness of food that impacts dietary behavior. Previous studies show that women focus on nutritional value of food [10] and prioritize healthy eating [7] more so than do men. We found that the foods or food components most commonly viewed as “very unhealthy” and most commonly avoided were sugar, food additives, alcohol, saturated fat and white flour. This is in line with previous findings that women perceive sweet foods as less healthy [11] and avoid consumption of high fat foods to a higher extent [7], compared to men. A Swedish national survey from 2016 showed that women perceive the risk of falling ill through harmful substances such as chemicals in their diet, as higher than men [12]. This might, at least in part, explain why women had more negative views on food additives such as sweetening, coloring and conserving agents. Though all approved food additives are considered safe for human consumption, our findings suggest that there is a widespread concern of the health effects of these substances.

It is noteworthy that both women and men (but women more so than men) had more negative views on food additives than of established dietary risk factors such as salt, saturated fat and alcohol. This is possibly due to the recent year’s trend toward eating “clean” [13], which refers to consumption of unprocessed, whole foods and sometimes the elimination of entire food groups (e.g. dairy, sugar or gluten) [14]. Though perceived as healthy by many [14], “clean eating” does not guarantee a high quality diet [15] and could be associated with disordered eating [16]. As women’s dietary behavior to a greater extent than men’s seems impacted by perceived healthiness and is more likely to change over time [17] –dietary fads might have a greater impact on women’s diet. Previous findings from the current research project showed that women were indeed more likely than men to keep a specific diet and attempt to lose weight [9]. This could also be a reflection of women’s greater tendency to be impacted by dietary fads and trends. The specific diet, or foods or food components that are avoided likely differs over time, but this needs verification in longitudinal studies.

The observed gender differences in the current and previous studies might have significant implications for public health. Findings are consistent that women are more health conscious than men –both in general [8] and in specific regards to their diet [7]. This might have parallel effects, where women eat healthier than men but also have more body shape concerns and diet-related anxiety. Perceived diet-related risks are assessed by both emotional and cognitive considerations, among both women and men [18]. Thereby, simply providing more information on diet and health is unlikely to eliminate gender differences in food perception and avoidance. More research is needed to identify effective ways of promoting healthy eating for both women and men, while minimizing diet-health related anxiety.

Strengths and limitation

Strengths of the current study include the relatively high response rate (28%) for this kind of study, and that the study sample is deemed population-representative. We have previously concluded that the sample seems representative of the general Swedish population in regards to prevalence of overweight and income, whereas the education level was slightly higher than the general Swedish population [9]. The proportions of women and men in the study are 55 and 45%, which indicated that women are slightly overrepresented (as the national gender distribution is 50% women, 50% men). Thus, there are small differences in sociodemographic data in this study sample, compared to the general population. The study results are thereby likely generalizable to the Swedish population in the current age span. Limitations include a lack of detailed dietary intake data to verify that reported food avoidance was also reflected in actual diet. In addition, a number of statistical tests were performed on several variables in this paper, and p-values should thereby be interpreted with caution. An additional limitation is the pre-specified answers that may have restricted the range of possible responses to the questions. Even though free text options were available, these were not frequently used. Future studies should consider combining quantitative and qualitative approaches to provide further clarity to the motivations for women’s more frequent food avoidance.

Female bias crime suspects are more likely than men to target friends & family members, to target other women, & more frequently commit crimes based on race/ethnicity/national origin than on religion or sexual orientation

Stotzer, R., Godinet, M.T. and Davidson, J.T., 2020. Unique Characteristics of Bias Crimes Committed by Males or Females in the United States. Journal of Hate Studies, 16(1), pp.35–47. http://doi.org/10.33972/jhs.153

Rolf Degen's bias: https://twitter.com/DegenRolf/status/1345240406884298753

Abstract: Despite increased research on women’s criminal offending patterns, research on women’s involvement in bias crimes is almost nonexistent. This study examines bias crime incidences that are considered crimes against persons (e.g., assault, murder, robbery, sexual assault) collected in the National Incidence-based Reporting System from 2009–2012 to determine what features characterize crimes committed by men or women. Results indicate that female bias crime suspects choose different victims than male suspects; female suspects are more likely than men to target friends and family members, more likely to target other women, and more frequently commit crimes based on race/ethnicity/national origin than religion or sexual orientation-based bias crimes, and were less likely to use a firearm. Men and women were similar in their suspect characteristics (such as using alcohol/drugs before the crime) and the overall incident characteristics (such as causing injury). These results suggest that we need to more critically examine current models of bias crime commission, and to include bias crimes as another avenue to help uncover differences in male and female offending.

Keywords: Bias crimes, Hate Crimes, Females, Perpetrators, Victims, Gender differences

Conclusions and Discussion

The results of this study of NIBRS data from 2009-2012 show that crimes against persons involving males and females who are suspects in bias crimes share many similar characteristics, but there are also important differences that deserve attention. Females demonstrated the greatest differences in their victim selection, being more likely than males to victimize their friends and family members, to victimize other women or a group of victims that include women, and were more likely to be motivated by a victim’s race/ethnicity/national origin than other bias types. However, incidents involving male and female offenders had similar suspect characteristics and incident characteristics outside of the use of weapons, suggesting the greatest difference between male and female bias crime offenders is how they select their victims.

While males and females demonstrated differences at the bivariate level in regard to the use of alcohol or other drugs before the commission of the crime and being in groups of suspects rather than acting alone, these differences did not retain statistical significance in the logistic regression. In regard to characteristics of the crime itself, bivariate statistics suggested women were more likely than men to commit their crimes in residences rather than public spaces. However, this difference in location was not significant in the logistic regression. While injury severity was statistically significant at the bivariate level, neither was significant in the logistic regression, but weapons use was significant with women being less likely than men to use a firearm.

Many of these differences reflect the differences between men and women who commit non-bias crimes. For example, men are more likely to use firearms in non-bias crimes than women, which held true among these bias crimes as well. Similar to the pattern of offending among non-bias crimes, women were more likely to victimize people they knew, particularly intimates, while men targeted strangers in a higher percentage. Also similar to non-bias crimes, female bias crime suspects victimized other women in higher percentages while men predominantly victimized other men.

New information uncovered in this analysis was the fact that women were overrepresented among bias crimes based on a victim’s race/ethnicity and underrepresented among bias crimes based on sexual orientation or religion. In these ways men and women may differ in their bias crime violence in ways that are similar to the ways that men and women differ in perpetrating non-bias crimes. And, too, women may also be exhibiting patterns that align with theories around multiple marginality, that gender, race, and class all intersect to shape the social space within which women commit crime (Chesney-Lind, 2006). These data cannot be used to explain why female bias crime offenders were more likely to commit crimes in residences, against individuals they knew, and without weapons. However, the general pattern of female offender restrictions within patriarchal structures would suggest that limited opportunities restrict their ability to commit bias crimes as well. In other words, gender roles and socialization may very well restrict the opportunities to commit both bias and non-bias crimes, so crimes are closer to home and without the benefit of weapons. A pathways perspective would also suggest that female bias crime offenders are more relational in their crime choices (Belknap & Holsinger, 2006).

A pathways perspective is useful in the interpretation of the important differences that emerged when comparing these results among bias crimes to the pattern of male and female offending in non-bias crimes. Female suspects were more likely to target victims in residences among non-bias crimes, and while that relationship held true among bias crimes at the bivariate level, this relationship did not emerge as significant in the regression analysis. Male suspects have also been found to cause more serious injury than female suspects in non-bias crimes, and again, this was found among non-bias crimes at the bivariate level, but not in the regression analysis. In these ways, male and female suspects may be more similar, and gender less of a predictive factor, when committing bias crime than when committing non-bias crimes.

While much more needs to be discovered in the area of gender and the commission of bias crimes, these findings are nonetheless interesting in light of the pathways approach to understand female offending, arguably the most prevalent model of analyzing and thinking about female crimes today. The pathways model, in the main, explains how histories of victimization often precede female offending, and how crimes are often linked to survival, physical or emotional (Belknap & Holsinger, 2006). In this light, non-bias crime offending for women can be thought of as a reaction to circumstances. Bias crimes are different, though. There is not always a tangible gain from the commission of a bias crime. These crimes are about motivation, and it is unclear whether, if at all, the traditional pathways approach can apply to bias crime offending. The nature of bias crimes makes it unlikely that crimes of this type are related to survival. Also unclear is whether female bias crime offenders might fit into one of the multiple pathways to crime as presented by Brennan, Breitenbach, Dieterich, Salisbury, and von Voorhis (2012) as they relate to the feminist pathways approach. Or, as Pezzella (2017) questions, perhaps additional categories need to be added to the McDevitt, Levin, and Bennet (2002) typology of bias offenders. The research in this area is too sparse, and new, to make that determination at this time.

While these results do not conclusively create a model for female’s participation in bias crimes, nor were they intended to, they nonetheless offer an important lens on the examination of bias crime, and offers avenues for future research to build theories for the gendered nature of bias crime involvement. Current theories around the gendered nature of bias crime has centered around men, both as victims and as offenders, these results highlight that bias crimes are not inherently the domain of men. Prior research into sexual orientation-based bias crimes has found that bias crimes are deeply intersectional (Meyer, 2008; 2010; Stotzer, 2010), and that race, class, and gender are often intertwined. Rather than looking at gender alone, this finding demonstrates a need to look more closely at how gender interacts with other factors in order to better explain why women target women and men target men during bias crime incidents.

While this study offers a preliminary glimpse into the differences between men and women’s pattern of bias crime offending, there are significant limitations to the study. First, a significant proportion of bias crimes are not reported to officials (Harlow, 2005), suggesting an initial bias in any official reports, including NIBRS, that may not capture the entire spectrum of bias crime. Second, while NIBRS is a significant improvement in data collection across the United States, it is not representative. Because of the laborious nature of processing incident-level reporting to the federal government, densely populated cities and states have not traditionally provided data to NIBRS. Thus, these findings might be generalizable to less dense jurisdictions rather than bias crimes that have been committed in dense urban locations. Third, the categorical nature of the data collection in NIBRS means that significant nuance in motives and crime characteristics have been lost. While some inferences can be drawn from the patterns in bias crime characteristics, additional research that can directly provide explanatory information are sorely needed. Fourth, as is typical with most large-scale, voluntary data collection efforts, missing data are a significant concern for generalizability. In particular, the variables related to weapons use and injury severity had the largest percentage of missing data compared to other variables in the analysis and limited the sample size. Fifth, the study was limited to crimes against persons since those crimes are more frequently able to identify a suspect compared to property crimes, such as vandalism, which are often discovered after the act has been completed. Given the large portion of bias crimes that are against property, particularly anti-Semitic bias crimes, this study cannot be generalized to bias crimes overall, only to those that are considered crimes against person. Last, while this study examined the unique characteristics of males and females, incidents that involved mixed gender groups of suspects were excluded. Future studies should examine to what degree these mixed gender groups share, or diverge from, the characteristics of men’s and women’s offending.

Taken together, these analyses suggest that current characterizations of bias crimes as occurring in public between strangers may have some viability for characterizing men’s participation in bias crimes, but does not adequately match the pattern of women’s offending. Similar to studies of non-bias crimes and the pattern of male and female offending, this study can directly identify how male and female offenders are similar or different, but can only indirectly offer possible explanations for why these differences exist. This research fills a current gap by informing what the nature of gendered bias crimes looks like. But, further research into female bias crime offenders can inform the current bias crime literature by expanding the understanding of offenders and their (gendered) motives. The sex differences in victim selection, rather than incident or offender characteristics, can also prove a fruitful area of additional research to further explore the differences between male and female offenders overall. However, there were also many similarities between men and women in the characteristics of their crime, and future research should begin isolating what factors may be driving these differences and what rewards and reinforces men’s and women’s bias crime offending.

Future research should employ a decidedly feminist approach, ensuring that female bias crime offenders are an intentional component of research, and that their voices are heard. Qualitative data of this nature are needed in order to inform the patterns demonstrated from this study. These types of data, merged with the quantitative data presented in this study, can create a foundation around which theory can begin to be built as well as an understanding of how, if at all, females ‘do gender’ in the commission of bias crimes.

Forecasts didn't cost Hillary Clinton votes among overconfident Democrats, but lowered turnout among Republicans confident their candidate would lose & stimulated turnout among Democrats confident their candidate would win

Revisiting the Link between Expected Election Outcomes and Turnout. Elizabeth C. Connors, Jacob A. Martin, John Barry Ryan. http://www.elizabethchaseconnors.com/images/Election%20Outcomes.pdf

Abstract: Westwood et al. (2020) causally demonstrate that probabilistic forecasts reduce beliefs about electoral competition, which, in turn, results in a lower propensity to vote. They argue this may have cost Hillary Clinton votes among overconfident supporters. Using the American National Election Study (ANES) from 2004 to 2016, we find that believing an election will not be close can affect turnout. The strongest evidence, however, suggests only those who believe their party’s candidate will lose by quite a bit are less likely to vote. Analysis of validated vote in 2016 does not support the conclusion that probabilistic forecasts cost Hillary Clinton votes among overconfident Democrats. The results suggest, if the probabilistic forecasts had any effect, they either lowered turnout among Republicans confident their candidate will lose or stimulated turnout among Democrats confident their candidate will win.