Taking a break: The effect of taking a vacation from Facebook and Instagram on subjective well-being. Sarah M. Hanley, Susan E. Watt, William Coventry. PLOS One, June 6, 2019. https://doi.org/10.1371/journal.pone.0217743
Abstract: Social Networking Sites (SNS) such as Facebook and Instagram have relocated a large portion of people’s social lives online, but can be intrusive and create social disturbances. Many people therefore consider taking an “SNS vacation.” We investigated the effects of a one-week vacation from both Facebook and Instagram on subjective well-being, and whether this would vary for passive or active SNS users. Usage amount was measured objectively, using RescueTime software, to circumvent issues of self-report. Usage style was identified at pre-test, and SNS users with a more active or more passive usage style were assigned in equal numbers to the conditions of one-week SNS vacation (n = 40) or no SNS vacation (n = 38). Subjective well-being (life satisfaction, positive affect, and negative affect) was measured before and after the vacation period. At pre-test, more active SNS use was found to correlate positively with life satisfaction and positive affect, whereas more passive SNS use correlated positively with life satisfaction, but not positive affect. Surprisingly, at post-test the SNS vacation resulted in lower positive affect for active users and had no significant effects for passive users. This result is contrary to popular expectation, and indicates that SNS usage can be beneficial for active users. We suggest that SNS users should be educated in the benefits of an active usage style and that future research should consider the possibility of SNS addiction among more active users.
Bipartisan Alliance, a Society for the Study of the US Constitution, and of Human Nature, where Republicans and Democrats meet.
Thursday, June 6, 2019
France Bans Judge Analytics, 5 Years In Prison For Rule Breakers
France Bans Judge Analytics, 5 Years In Prison For Rule Breakers. Artificial Lawyer, June 4 2019. https://www.artificiallawyer.com/2019/06/04/france-bans-judge-analytics-5-years-in-prison-for-rule-breakers/
Excerpts without links:
In a startling intervention that seeks to limit the emerging litigation analytics and prediction sector, the French Government has banned the publication of statistical information about judges’ decisions – with a five year prison sentence set as the maximum punishment for anyone who breaks the new law.
Owners of legal tech companies focused on litigation analytics are the most likely to suffer from this new measure.
The new law, encoded in Article 33 of the Justice Reform Act, is aimed at preventing anyone – but especially legal tech companies focused on litigation prediction and analytics – from publicly revealing the pattern of judges’ behaviour in relation to court decisions.
A key passage of the new law states:
‘The identity data of magistrates and members of the judiciary cannot be reused with the purpose or effect of evaluating, analysing, comparing or predicting their actual or alleged professional practices.’ *
[...]
Insiders in France told Artificial Lawyer that the new law is a direct result of an earlier effort to make all case law easily accessible to the general public, which was seen at the time as improving access to justice and a big step forward for transparency in the justice sector.
However, judges in France had not reckoned on NLP and machine learning companies taking the public data and using it to model how certain judges behave in relation to particular types of legal matter or argument, or how they compare to other judges.
In short, they didn’t like how the pattern of their decisions – now relatively easy to model – were potentially open for all to see.
Unlike in the US and the UK, where judges appear to have accepted the fait accompli of legal AI companies analysing their decisions in extreme detail and then creating models as to how they may behave in the future, French judges have decided to stamp it out.
Various reasons for this move have been shared on the Paris legal tech grapevine, ranging from the general need for anonymity, to the fear among judges that their decisions may reveal too great a variance from expected Civil Law norms.
One legal tech expert in France, who wished to remain anonymous, told Artificial Lawyer: ‘In the past few years there has been a growing debate in France about whether the names of judges should be removed from the decisions when those decisions are published online. The proponents of this view obtained this [new law] as a compromise from the Government, i.e. that judges’ names shouldn’t be redacted (with some exceptions to be determined) but that they cannot be used for statistical purposes.’
Whatever the reason, the law is now in effect and legal tech experts in Paris have told Artificial Lawyer that, as far as they interpret the regulations, anyone breaking the new rule can face up to five years in prison – which has to be the harshest example of legal tech regulation on the planet right now.
Forbidden knowledge…….
That said, French case law publishers, and AI litigation prediction companies, such as Prédictice, appear to be ‘doing OK’ without this specific information being made available. This is perhaps because even if you take out the judges from the equation there is still enough information remaining from the rest of the case law material to be of use.
Moreover, it’s unclear if a law firm, if asked to by a client, could not manually, or using an NLP system, collect data on a judge’s behaviour over many previous cases and create a statistical model for use by that client, as long as they didn’t then publish this to any third party. That said, it’s not clear this would be OK either. And with five years in prison hanging over your head, would anyone want to take the risk?
But, the point remains: a government and its justice system have decided to make it a crime for information about how its judges think about certain legal issues to be revealed in terms of statistical and comparative analysis.
Some of the French legal experts Artificial Lawyer talked to this week asked what this site’s perspective was. Well, if you really want to know, it’s this:
[...]
—
Part of the French text covering the new law is below:
‘Les données d’identité des magistrats et des membres du greffe ne peuvent faire l’objet d’une réutilisation ayant pour objet ou pour effet d’évaluer, d’analyser, de comparer ou de prédire leurs pratiques professionnelles réelles ou supposées.
La violation de cette interdiction est punie des peines prévues aux articles 226-18, 226-24 et 226-31 du code pénal, sans préjudice des mesures et sanctions prévues par la loi n° 78-17 du 6 janvier 1978 relative à l’informatique, aux fichiers et aux libertés.’
(* Translated version above, via Google.)
Excerpts without links:
In a startling intervention that seeks to limit the emerging litigation analytics and prediction sector, the French Government has banned the publication of statistical information about judges’ decisions – with a five year prison sentence set as the maximum punishment for anyone who breaks the new law.
Owners of legal tech companies focused on litigation analytics are the most likely to suffer from this new measure.
The new law, encoded in Article 33 of the Justice Reform Act, is aimed at preventing anyone – but especially legal tech companies focused on litigation prediction and analytics – from publicly revealing the pattern of judges’ behaviour in relation to court decisions.
A key passage of the new law states:
‘The identity data of magistrates and members of the judiciary cannot be reused with the purpose or effect of evaluating, analysing, comparing or predicting their actual or alleged professional practices.’ *
[...]
Insiders in France told Artificial Lawyer that the new law is a direct result of an earlier effort to make all case law easily accessible to the general public, which was seen at the time as improving access to justice and a big step forward for transparency in the justice sector.
However, judges in France had not reckoned on NLP and machine learning companies taking the public data and using it to model how certain judges behave in relation to particular types of legal matter or argument, or how they compare to other judges.
In short, they didn’t like how the pattern of their decisions – now relatively easy to model – were potentially open for all to see.
Unlike in the US and the UK, where judges appear to have accepted the fait accompli of legal AI companies analysing their decisions in extreme detail and then creating models as to how they may behave in the future, French judges have decided to stamp it out.
Various reasons for this move have been shared on the Paris legal tech grapevine, ranging from the general need for anonymity, to the fear among judges that their decisions may reveal too great a variance from expected Civil Law norms.
One legal tech expert in France, who wished to remain anonymous, told Artificial Lawyer: ‘In the past few years there has been a growing debate in France about whether the names of judges should be removed from the decisions when those decisions are published online. The proponents of this view obtained this [new law] as a compromise from the Government, i.e. that judges’ names shouldn’t be redacted (with some exceptions to be determined) but that they cannot be used for statistical purposes.’
Whatever the reason, the law is now in effect and legal tech experts in Paris have told Artificial Lawyer that, as far as they interpret the regulations, anyone breaking the new rule can face up to five years in prison – which has to be the harshest example of legal tech regulation on the planet right now.
Forbidden knowledge…….
That said, French case law publishers, and AI litigation prediction companies, such as Prédictice, appear to be ‘doing OK’ without this specific information being made available. This is perhaps because even if you take out the judges from the equation there is still enough information remaining from the rest of the case law material to be of use.
Moreover, it’s unclear if a law firm, if asked to by a client, could not manually, or using an NLP system, collect data on a judge’s behaviour over many previous cases and create a statistical model for use by that client, as long as they didn’t then publish this to any third party. That said, it’s not clear this would be OK either. And with five years in prison hanging over your head, would anyone want to take the risk?
But, the point remains: a government and its justice system have decided to make it a crime for information about how its judges think about certain legal issues to be revealed in terms of statistical and comparative analysis.
Some of the French legal experts Artificial Lawyer talked to this week asked what this site’s perspective was. Well, if you really want to know, it’s this:
[...]
—
Part of the French text covering the new law is below:
‘Les données d’identité des magistrats et des membres du greffe ne peuvent faire l’objet d’une réutilisation ayant pour objet ou pour effet d’évaluer, d’analyser, de comparer ou de prédire leurs pratiques professionnelles réelles ou supposées.
La violation de cette interdiction est punie des peines prévues aux articles 226-18, 226-24 et 226-31 du code pénal, sans préjudice des mesures et sanctions prévues par la loi n° 78-17 du 6 janvier 1978 relative à l’informatique, aux fichiers et aux libertés.’
(* Translated version above, via Google.)
Minimum Wage and Productivity: A real increase of about 22% in the minimum wage during the period 1998–2000 reduced TFP by 5.8% in low unskilled-intensive industries and 9.7% in high unskilled-intensive industries in Chile
Minimum Wage and Productivity: Evidence from Chilean Manufacturing Plants. Roberto Álvarez, Rodrigo Fuentes. Economic Development and Cultural Change, Volume 67, Number 1 | October 2018, pp. 193–224. https://www.journals.uchicago.edu/doi/abs/10.1086/697557
Abstract: This paper analyzes the effects of the minimum wage on a firm’s productivity. The main hypothesis is that an increase in the minimum wage has a negative effect on total factor productivity (TFP) due to the existence of labor adjustment costs. Using data from Chilean manufacturing plants for the period 1992–2005 and a difference-in-differences methodology, we find that an increase in minimum wage had a negative effect on TFP. Our estimates indicate that a real increase of about 22% in the minimum wage during the period 1998–2000 reduced TFP by 5.8% in low unskilled-intensive industries and 9.7% in high unskilled-intensive industries. These results are robust to alternative measures of productivity and to the inclusion of several covariates to avoid confounding effects of other policy changes or firms’ exposure to minimum wage changes.
Abstract: This paper analyzes the effects of the minimum wage on a firm’s productivity. The main hypothesis is that an increase in the minimum wage has a negative effect on total factor productivity (TFP) due to the existence of labor adjustment costs. Using data from Chilean manufacturing plants for the period 1992–2005 and a difference-in-differences methodology, we find that an increase in minimum wage had a negative effect on TFP. Our estimates indicate that a real increase of about 22% in the minimum wage during the period 1998–2000 reduced TFP by 5.8% in low unskilled-intensive industries and 9.7% in high unskilled-intensive industries. These results are robust to alternative measures of productivity and to the inclusion of several covariates to avoid confounding effects of other policy changes or firms’ exposure to minimum wage changes.
A man with an unattractive wife is perceived to be more moral because the couple shares a stronger & more communal relationship
Forming Judgments Based on Spouse’s Attractiveness. Nivriti Chowdhry, Ajay Kalra. European Association for Consumer Research Conference Proceedings, Volume 11, 2018. http://www3.acrwebsite.org/assets/PDFs/Proceedings/EACRVol11.pdf
Excerpts of the extended abstract:
This research investigates the effect of spouse attractiveness on the perceived morality of a focal person and the credibility of their firm. Five studies demonstrate that a man with an unattractive wife is perceived to be more moral because the couple shares a stronger and more communal relationship.The spouses and romantic partners of CEOs, politicians, and celebrities are often in the public eye themselves. For example, Melinda Gates, Priscilla Chan, and Miranda Kerr are as well-known as their spouses. Additionally, several service providers and retailers (e.g., financial advisors, contractors, automobile dealers) routinely feature their spouses in their professional profiles and commercial messages. How does the beauty of the spouse impact perceptions of the focal person?The person perception literature concludes that, in general, beautiful people reap more benefits from society than unattractive people (Dion, Berscheid, and Walster 1972, Langlois et al. 2000, Mobius and Rosenblat 2006). This research focuses on the effects of a person’s own beauty, not the beauty of people associated with a target person. In contrast, we demonstrate that judgments about a fo-cal person’s traits can be based on the attractiveness of their spouse, and explicate why an associated person’s physical attractiveness can be detrimental to perceptions of a focal person. In particular, using entitativity theory and social exchange theory, we explain how the physical appearance of an associated person can signal information about a target person’s morality, one of the more important dimension in marketing and consumer behavior.
Entitativity is defined as the cohesiveness and unity of a social group, such as a sports team, work group, or family (Campbell 1958; McConnell et al. 1997). When gauging the entitativity of a group, judges may consider fixed characteristics or dynamic processes un-derlying the relationship (Wai-man Ip, Chiu, and Wan 2006). Fixed characteristics are immediately observable physical features and signal psychological similarity. Dynamic processes underlying the relationship include the behavior and movement patterns of a group and signal common goals and attitudes of the group members (Wai-man Ip et al. 2006).
Social exchange theory (Blau 1964) posits that married couples exchange physical attractiveness, social status, and wealth. Of these, physical attractiveness is the only immediately observable fixed characteristic that entitativity judgments about a married couple can be based on. There are three different combinations of a married cou-ple’s relative attractiveness: (a) a physically similar couple, in which both people are equally attractive, (b) when the wife is more attrac-tive than the husband, and (c) when the husband is more attractive than the wife. The first combination - two equally attractive people - is consistent with extant entitativity theory. When both individu-als in a relationship are similarly attractive, they indicate entitativity through fixed characteristics, and are likely perceived to be psycho-logically similar. The second pairing has been studied and concludes that men married to attractive women are perceived to exchange wealth or social status for physical attractiveness (Baumeister and Vohs 2004).
Excerpts of the extended abstract:
This research investigates the effect of spouse attractiveness on the perceived morality of a focal person and the credibility of their firm. Five studies demonstrate that a man with an unattractive wife is perceived to be more moral because the couple shares a stronger and more communal relationship.The spouses and romantic partners of CEOs, politicians, and celebrities are often in the public eye themselves. For example, Melinda Gates, Priscilla Chan, and Miranda Kerr are as well-known as their spouses. Additionally, several service providers and retailers (e.g., financial advisors, contractors, automobile dealers) routinely feature their spouses in their professional profiles and commercial messages. How does the beauty of the spouse impact perceptions of the focal person?The person perception literature concludes that, in general, beautiful people reap more benefits from society than unattractive people (Dion, Berscheid, and Walster 1972, Langlois et al. 2000, Mobius and Rosenblat 2006). This research focuses on the effects of a person’s own beauty, not the beauty of people associated with a target person. In contrast, we demonstrate that judgments about a fo-cal person’s traits can be based on the attractiveness of their spouse, and explicate why an associated person’s physical attractiveness can be detrimental to perceptions of a focal person. In particular, using entitativity theory and social exchange theory, we explain how the physical appearance of an associated person can signal information about a target person’s morality, one of the more important dimension in marketing and consumer behavior.
Entitativity is defined as the cohesiveness and unity of a social group, such as a sports team, work group, or family (Campbell 1958; McConnell et al. 1997). When gauging the entitativity of a group, judges may consider fixed characteristics or dynamic processes un-derlying the relationship (Wai-man Ip, Chiu, and Wan 2006). Fixed characteristics are immediately observable physical features and signal psychological similarity. Dynamic processes underlying the relationship include the behavior and movement patterns of a group and signal common goals and attitudes of the group members (Wai-man Ip et al. 2006).
Social exchange theory (Blau 1964) posits that married couples exchange physical attractiveness, social status, and wealth. Of these, physical attractiveness is the only immediately observable fixed characteristic that entitativity judgments about a married couple can be based on. There are three different combinations of a married cou-ple’s relative attractiveness: (a) a physically similar couple, in which both people are equally attractive, (b) when the wife is more attrac-tive than the husband, and (c) when the husband is more attractive than the wife. The first combination - two equally attractive people - is consistent with extant entitativity theory. When both individu-als in a relationship are similarly attractive, they indicate entitativity through fixed characteristics, and are likely perceived to be psycho-logically similar. The second pairing has been studied and concludes that men married to attractive women are perceived to exchange wealth or social status for physical attractiveness (Baumeister and Vohs 2004).
Girls perform better than boys on performance-based ICT literacy assessments; differences are larger in primary schools than in secondary schools; overall, the gender differences in ICT literacy are significant but small
Is there a gender gap? A meta-analysis of the gender differences in students' ICT literacy. Fazilat Siddiq, Ronny Scherer. Educational Research Review, Volume 27, June 2019, Pages 205-217. https://doi.org/10.1016/j.edurev.2019.03.007
Highlights
• Girls perform better than boys on performance-based ICT literacy assessments.
• Gender differences are larger in primary schools than in secondary schools.
• The overall effect size is robust across several analysis conditions.
• No evidence of publication bias could be found.
• Overall, the gender differences in ICT literacy are significant but small.
Abstract: The study of gender differences in academic achievement has been one of the core topics in education, especially because it may uncover possible gaps and inequalities in certain domains. Whereas these differences have largely been examined in traditional domains, such as mathematics, reading, and science, the existing body of empirical studies in the domain of ICT literacy is considerably smaller, yet abounds in diverse findings. One of the persistent findings however is that boys consider their ICT literacy to be higher than that of girls. This meta-analysis tests whether the same pattern holds for students’ actual performance on ICT literacy tasks, as measured by performance-based assessments. In total, 46 effect sizes were extracted from 23 empirical studies using a random-effects model. Overall, the gender differences in ICT literacy were significant, positive, and favored girls (g = + 0.12, 95 % CI = [0.08, 0.16]). This effect varied between studies, and moderation analyses indicated that the grade level students were taught at moderated its magnitude—effect sizes were larger in primary school as compared to secondary school. In conclusion, our findings contrast those obtained from previous meta-analyses that were based on self-reported ICT literacy and suggest that the ICT gender gap may not be as severe as it had been claimed to be.
Highlights
• Girls perform better than boys on performance-based ICT literacy assessments.
• Gender differences are larger in primary schools than in secondary schools.
• The overall effect size is robust across several analysis conditions.
• No evidence of publication bias could be found.
• Overall, the gender differences in ICT literacy are significant but small.
Abstract: The study of gender differences in academic achievement has been one of the core topics in education, especially because it may uncover possible gaps and inequalities in certain domains. Whereas these differences have largely been examined in traditional domains, such as mathematics, reading, and science, the existing body of empirical studies in the domain of ICT literacy is considerably smaller, yet abounds in diverse findings. One of the persistent findings however is that boys consider their ICT literacy to be higher than that of girls. This meta-analysis tests whether the same pattern holds for students’ actual performance on ICT literacy tasks, as measured by performance-based assessments. In total, 46 effect sizes were extracted from 23 empirical studies using a random-effects model. Overall, the gender differences in ICT literacy were significant, positive, and favored girls (g = + 0.12, 95 % CI = [0.08, 0.16]). This effect varied between studies, and moderation analyses indicated that the grade level students were taught at moderated its magnitude—effect sizes were larger in primary school as compared to secondary school. In conclusion, our findings contrast those obtained from previous meta-analyses that were based on self-reported ICT literacy and suggest that the ICT gender gap may not be as severe as it had been claimed to be.
The Puzzle of Open Defecation in Rural India: Evidence from a Novel Measure of Caste Attitudes in a Nationally Representative Survey
The Puzzle of Open Defecation in Rural India: Evidence from a Novel Measure of Caste Attitudes in a Nationally Representative Survey. Dean Spears. Economic Development and Cultural Change, May 30, 2019. https://www.journals.uchicago.edu/doi/abs/10.1086/698852
Abstract: Uniquely widespread and persistent open defecation in rural India has emerged as an important policy challenge and puzzle about behavioral choice in economic development. One candidate explanation is the culture of purity and pollution that reinforces and has its origins in the caste system. Although such a cultural account is inherently difficult to quantitatively test, we provide support for this explanation by comparing open defecation rates across places in India where untouchability is more and less intensely practiced. In particular, we exploit a novel question in the 2012 India Human Development Survey that asked households whether they practice untouchability, meaning whether they enforce norms of purity and pollution in their interactions with lower castes. We find an association between local practice of untouchability and open defecation that is robust; is not explained by economic, educational, or other observable differences; and is specific to open defecation rather than other health behavior or human capital investments more generally. We verify that practicing untouchability is not associated with general disadvantage in health knowledge or access to medical professionals. We interpret this as evidence that the culture of purity, pollution, untouchability, and caste contributes to the exceptional prevalence of open defecation in rural India.
Abstract: Uniquely widespread and persistent open defecation in rural India has emerged as an important policy challenge and puzzle about behavioral choice in economic development. One candidate explanation is the culture of purity and pollution that reinforces and has its origins in the caste system. Although such a cultural account is inherently difficult to quantitatively test, we provide support for this explanation by comparing open defecation rates across places in India where untouchability is more and less intensely practiced. In particular, we exploit a novel question in the 2012 India Human Development Survey that asked households whether they practice untouchability, meaning whether they enforce norms of purity and pollution in their interactions with lower castes. We find an association between local practice of untouchability and open defecation that is robust; is not explained by economic, educational, or other observable differences; and is specific to open defecation rather than other health behavior or human capital investments more generally. We verify that practicing untouchability is not associated with general disadvantage in health knowledge or access to medical professionals. We interpret this as evidence that the culture of purity, pollution, untouchability, and caste contributes to the exceptional prevalence of open defecation in rural India.