Welcome to the Nexus of Ethics, Psychology, Morality, Philosophy and Health Care

Welcome to the nexus of ethics, psychology, morality, technology, health care, and philosophy
Showing posts with label Discrimination. Show all posts
Showing posts with label Discrimination. Show all posts

Thursday, December 7, 2023

How moral bioenhancement affects perceived praiseworthiness

Lucas, S., Douglas, T., & Faber, N. S. (2023).


Psychological literature indicates that actions performed with the assistance of cognition-enhancing biomedical technologies are often deemed to be less praiseworthy than similar actions performed without such assistance. This study examines (i) whether this result extends to the bioenhancement of moral capacities, and (ii) if so, what explains the effect of moral bioenhancement on perceived praiseworthiness. The findings indicate that actions facilitated by morally bioenhanced individuals are considered less deserving of praise than similar actions facilitated by ‘traditional’ moral enhancement—for example, moral self-education. This diminished praise does not seem to be driven by an aversion to (moral) bioenhancement per se. Instead, it appears to be primarily attributable to a perceived lack of effort exerted by bioenhanced individuals in the course of their moral enhancement. Our findings advance the philosophical discourse on the foundations of praise in the context of moral bioenhancement by elucidating the empirical basis underlying some assumptions commonly employed to argue for or against the permissibility of moral bioenhancement.

It is an open source article.  Link above works.

My summary:

This research shows whether people are less likely to praise morally bioenhanced individuals for their actions. The authors found that people do perceive morally bioenhanced individuals as less deserving of praise than those who achieve moral enhancement through traditional means, such as moral self-education.

The authors argue that this diminished praise is not due to an aversion to moral bioenhancement per se, but rather to a perceived lack of effort on the part of the bioenhanced individual. In other words, people believe that bioenhanced individuals have not had to work as hard to achieve their moral excellence, and therefore deserve less praise for their accomplishments.

This finding has important implications for the development and use of moral bioenhancement technologies. If people are less likely to praise morally bioenhanced individuals, it could lead to a number of negative consequences, such as social stigma and discrimination. Additionally, it could discourage people from using moral bioenhancement technologies, even if they believe that these technologies could help them to become more moral people.

Sunday, December 3, 2023

ChatGPT one year on: who is using it, how and why?

Ghassemi, M., Birhane, A., et al.
Nature 624, 39-41 (2023)
doi: https://doi.org/10.1038/d41586-023-03798-6

Here is an excerpt:

More pressingly, text and image generation are prone to societal biases that cannot be easily fixed. In health care, this was illustrated by Tessa, a rule-based chatbot designed to help people with eating disorders, run by a US non-profit organization. After it was augmented with generative AI, the now-suspended bot gave detrimental advice. In some US hospitals, generative models are being used to manage and generate portions of electronic medical records. However, the large language models (LLMs) that underpin these systems are not giving medical advice and so do not require clearance by the US Food and Drug Administration. This means that it’s effectively up to the hospitals to ensure that LLM use is fair and accurate. This is a huge concern.

The use of generative AI tools, in general and in health settings, needs more research with an eye towards social responsibility rather than efficiency or profit. The tools are flexible and powerful enough to make billing and messaging faster — but a naive deployment will entrench existing equity issues in these areas. Chatbots have been found, for example, to recommend different treatments depending on a patient’s gender, race and ethnicity and socioeconomic status (see J. Kim et al. JAMA Netw. Open 6, e2338050; 2023).

Ultimately, it is important to recognize that generative models echo and extend the data they have been trained on. Making generative AI work to improve health equity, for instance by using empathy training or suggesting edits that decrease biases, is especially important given how susceptible humans are to convincing, and human-like, generated texts. Rather than taking the health-care system we have now and simply speeding it up — with the risk of exacerbating inequalities and throwing in hallucinations — AI needs to target improvement and transformation.

Here is my summary:

The article on ChatGPT's one-year anniversary presents a comprehensive analysis of its usage, exploring the diverse user base, applications, and underlying motivations driving its adoption. It reveals that ChatGPT has found traction across a wide spectrum of users, including writers, developers, students, professionals, and hobbyists. This broad appeal can be attributed to its adaptability in assisting with a myriad of tasks, from generating creative content to aiding in coding challenges and providing language translation support.

The analysis further dissects how users interact with ChatGPT, showcasing distinct patterns of utilization. Some users leverage it for brainstorming ideas, drafting content, or generating creative writing, while others turn to it for programming assistance, using it as a virtual coding companion. Additionally, the article explores the strategies users employ to enhance the model's output, such as providing more context or breaking down queries into smaller parts.  There are still issues with biases, inaccurate information, and inappropriate uses.

Wednesday, November 29, 2023

A justification-suppression model of the expression and experience of prejudice

Crandall, C. S., & Eshleman, A. (2003).
Psychological bulletin, 129(3), 414–446.


The authors propose a justification-suppression model (JSM), which characterizes the processes that lead to prejudice expression and the experience of one's own prejudice. They suggest that "genuine" prejudices are not directly expressed but are restrained by beliefs, values, and norms that suppress them. Prejudices are expressed when justifications (e.g., attributions, ideologies, stereotypes) release suppressed prejudices. The same process accounts for which prejudices are accepted into the self-concept The JSM is used to organize the prejudice literature, and many empirical findings are recharacterized as factors affecting suppression or justification, rather than directly affecting genuine prejudice. The authors discuss the implications of the JSM for several topics, including prejudice measurement, ambivalence, and the distinction between prejudice and its expression.

This is an oldie, but goodie!!  Here is my summary:

This article is about prejudice and the factors that influence its expression. The authors propose a justification-suppression model (JSM) to explain how prejudice is expressed. The JSM suggests that people have genuine prejudices that are not directly expressed. Instead, these prejudices are suppressed by people’s beliefs, values, and norms. Prejudice is expressed when justifications (e.g., attributions, ideologies, stereotypes) release suppressed prejudices.

The authors also discuss the implications of the JSM for prejudice measurement, ambivalence, and the distinction between prejudice and its expression.

Here are some key takeaways from the article:
  • Prejudice is a complex phenomenon that is influenced by a variety of factors, including individual beliefs, values, and norms, as well as social and cultural contexts.
  • People may have genuine prejudices that they do not directly express. These prejudices may be suppressed by people’s beliefs, values, and norms.
  • Prejudice is expressed when justifications (e.g., attributions, ideologies, stereotypes) release suppressed prejudices.
  • The JSM can be used to explain a wide range of findings on prejudice, including prejudice measurement, ambivalence, and the distinction between prejudice and its expression.

Wednesday, November 15, 2023

Private UK health data donated for medical research shared with insurance companies

Shanti Das
The Guardian
Originally poste 12 Nov 23

Sensitive health information donated for medical research by half a million UK citizens has been shared with insurance companies despite a pledge that it would not be.

An Observer investigation has found that UK Biobank opened up its vast biomedical database to insurance sector firms several times between 2020 and 2023. The data was provided to insurance consultancy and tech firms for projects to create digital tools that help insurers predict a person’s risk of getting a chronic disease. The findings have raised concerns among geneticists, data privacy experts and campaigners over vetting and ethical checks at Biobank.

Set up in 2006 to help researchers investigating diseases, the database contains millions of blood, saliva and urine samples, collected regularly from about 500,000 adult volunteers – along with medical records, scans, wearable device data and lifestyle information.

Approved researchers around the world can pay £3,000 to £9,000 to access records ranging from medical history and lifestyle information to whole genome sequencing data. The resulting research has yielded major medical discoveries and led to Biobank being considered a “jewel in the crown” of British science.

Biobank said it strictly guarded access to its data, only allowing access by bona fide researchers for health-related projects in the public interest. It said this included researchers of all stripes, whether employed by academic, charitable or commercial organisations – including insurance companies – and that “information about data sharing was clearly set out to participants at the point of recruitment and the initial assessment”.

Here is my summary:

Private health data donated by over half a million UK citizens for medical research has been shared with insurance companies, despite a pledge that it would not be used for this purpose. The data, which includes genetic information, medical diagnoses, and lifestyle factors, has been used to develop digital tools that help insurers predict a person's risk of getting a chronic disease. This raises concerns about the privacy and security of sensitive health data, as well as the potential for insurance companies to use the data to discriminate against people with certain health conditions.

Tuesday, August 29, 2023

Yale University settles lawsuit alleging it pressured students with mental health issues to withdraw

Associated Press
Originally posted 25 Aug 23

Yale University and a student group announced Friday that they've reached a settlement in a federal lawsuit that accused the Ivy League school of discriminating against students with mental health disabilities, including pressuring them to withdraw.

Under the agreement, Yale will modify its policies regarding medical leaves of absence, including streamlining the reinstatement process for students who return to campus. The student group, which also represents alumni, had argued the process was onerous, discouraging students for decades from taking medical leave when they needed it most.

The settlement is a “watershed moment” for the university and mental health patients, said 2019 graduate Rishi Mirchandani, a co-founder of Elis for Rachael, the group that sued. It was formed to help students with mental health issues in honor of a Yale student who took her own life.

“This historic settlement affirms that students with mental health needs truly belong," Mirchandani said.

A joint statement from Elis for Rachael and Yale, released on Friday, confirmed the agreement "to resolve a lawsuit filed last November in federal district court related to policies and practices impacting students with mental health disabilities.”

Under the agreement, Yale will allow students to study part-time if they have urgent medical needs. Elis for Rachael said it marks the first time the university has offered such an option. Students granted the accommodation at the beginning of a new term will receive a 50% reduction in tuition.

“Although Yale describes the circumstances for this accommodation as ‘rare,’ this change still represents a consequential departure from the traditional all-or-nothing attitude towards participation in academic life at Yale,” the group said in a statement.

The dean of Yale College, Pericles Lewis, said he was “pleased with today’s outcome.”

The potential good news: The lawsuit against Yale is a step towards ensuring that students with mental health disabilities have the same opportunities as other students. It is also a reminder that colleges and universities have a responsibility to create a supportive environment for all students, regardless of their mental health status.

Saturday, July 29, 2023

Racism in the Hands of an Angry God: How Image of God Impacts Cultural Racism in Relation to Police Treatment of African Americans

Lauve‐Moon, T. A., & Park, J. Z. (2023).
Journal for the Scientific Study of Religion.


Previous research suggests an angry God image is a narrative schema predicting support for more punitive forms of criminal justice. However, this research has not explored the possibility that racialization may impact one's God image. We perform logistic regression on Wave V of the Baylor Religion Survey to examine the correlation between an angry God image and the belief that police shoot Blacks more often because Blacks are more violent than Whites (a context-specific form of cultural racism). Engaging critical insights from intersectionality theory, we also interact angry God image with both racialized identity and racialized religious tradition. Results suggest that the angry God schema is associated with this form of cultural racism for White people generally as well as White Evangelicals, yet for Black Protestants, belief in an angry God is associated with resistance against this type of cultural racism.


Despite empirical evidence demonstrating the persistence of implicit bias in policing and institutional racism within law enforcement, the public continues to be divided on how to interpret police treatment of Black persons. This study uncovers an association between religious narrative schema, such as image of God, and one's attitude toward this social issue as well as how complex religion at the intersection of race and religious affiliation may impact the direction of this association between an angry God image and police treatment of Black persons. Our findings confirm that an angry God image is modestly associated with the narrative that police shoot Blacks more than Whites because Blacks are more violent than Whites. Even when controlling for other religious, political, and demographic factors, the association holds. While angry God is not the only factor or the most influential, our results suggests that it does work as a distinct factor in this understanding of police treatment of Black persons. Previous research supports this finding since the narrative that police shoot Blacks more because Blacks are more violent than Whites is based on punitive ideology. But whose version of the story is this telling?

Due to large White samples in most survey research, we contend that previous research has undertheorized the role that race plays in the association between angry God and punitive attitudes, and as a result, this research has likely inadvertently privileged a White narrative of angry God. Using the insights of critical quantitative methodology and intersectionality, the inclusion of interactions of angry God image with racialized identity as well as racialized religious traditions creates space for the telling of counternarratives regarding angry God image and the view that police shoot Blacks more than Whites because Blacks are more violent than Whites. The first interaction introduced assesses if racialized identity moderates the angry God effect. Although the interaction term for racialized identity and angry God is not significant, the predicted probabilities and average marginal effects elucidate a trend worth noting. While angry God image has no effect for Black respondents, it has a notable positive trend for White respondents, and this difference is pronounced on the higher half of the angry God scale. This supports our claim that past research has treated angry God image as a colorblind concept, yet this positive association between angry God and punitive criminal justice is raced, specifically raced White.

Here is a summary:

The article explores the relationship between image of God (IoG) and cultural racism in relation to police treatment of African Americans. The authors argue that IoG can be a source of cultural racism, which is a form of racism that is embedded in the culture of a society. They suggest that people who hold an angry IoG are more likely to believe that African Americans are dangerous and violent, and that this belief can lead to discriminatory treatment by police.

Here are some of the key points from the article:
  • Image of God (IoG) can be a source of cultural racism.
  • People who hold an angry IoG are more likely to believe that African Americans are dangerous and violent.
  • This belief can lead to discriminatory treatment by police.
  • Interventions that address IoG could be an effective way to reduce racism and discrimination.

Saturday, December 31, 2022

AI’s fairness problem: understanding wrongful discrimination in the context of automated decision-making

Cossette-Lefebvre, H., Maclure, J. 
AI Ethics (2022).


The use of predictive machine learning algorithms is increasingly common to guide or even take decisions in both public and private settings. Their use is touted by some as a potentially useful method to avoid discriminatory decisions since they are, allegedly, neutral, objective, and can be evaluated in ways no human decisions can. By (fully or partly) outsourcing a decision process to an algorithm, it should allow human organizations to clearly define the parameters of the decision and to, in principle, remove human biases. Yet, in practice, the use of algorithms can still be the source of wrongful discriminatory decisions based on at least three of their features: the data-mining process and the categorizations they rely on can reconduct human biases, their automaticity and predictive design can lead them to rely on wrongful generalizations, and their opaque nature is at odds with democratic requirements. We highlight that the two latter aspects of algorithms and their significance for discrimination are too often overlooked in contemporary literature. Though these problems are not all insurmountable, we argue that it is necessary to clearly define the conditions under which a machine learning decision tool can be used. We identify and propose three main guidelines to properly constrain the deployment of machine learning algorithms in society: algorithms should be vetted to ensure that they do not unduly affect historically marginalized groups; they should not systematically override or replace human decision-making processes; and the decision reached using an algorithm should always be explainable and justifiable.

From the Conclusion

Given that ML algorithms are potentially harmful because they can compound and reproduce social inequalities, and that they rely on generalization disregarding individual autonomy, then their use should be strictly regulated. Yet, these potential problems do not necessarily entail that ML algorithms should never be used, at least from the perspective of anti-discrimination law. Rather, these points lead to the conclusion that their use should be carefully and strictly regulated. However, before identifying the principles which could guide regulation, it is important to highlight two things. First, the context and potential impact associated with the use of a particular algorithm should be considered. Anti-discrimination laws do not aim to protect from any instances of differential treatment or impact, but rather to protect and balance the rights of implicated parties when they conflict [18, 19]. Hence, using ML algorithms in situations where no rights are threatened would presumably be either acceptable or, at least, beyond the purview of anti-discriminatory regulations.

Second, one also needs to take into account how the algorithm is used and what place it occupies in the decision-making process. More precisely, it is clear from what was argued above that fully automated decisions, where a ML algorithm makes decisions with minimal or no human intervention in ethically high stakes situation—i.e., where individual rights are potentially threatened—are presumably illegitimate because they fail to treat individuals as separate and unique moral agents. To avoid objectionable generalization and to respect our democratic obligations towards each other, a human agent should make the final decision—in a meaningful way which goes beyond rubber-stamping—or a human agent should at least be in position to explain and justify the decision if a person affected by it asks for a revision. If this does not necessarily preclude the use of ML algorithms, it suggests that their use should be inscribed in a larger, human-centric, democratic process.

Friday, November 25, 2022

White (but Not Black) Americans Continue to See Racism as a Zero-Sum Game; White Conservatives (but Not Moderates or Liberals) See Themselves as Losing

Rasmussen, R., Levari, D. E.,  et al.
Perspectives on Psychological Science, 0(0).


In a 2011 article in this journal entitled “Whites See Racism as a Zero-Sum Game That They Are Now Losing” (Perspectives on Psychological Science, 6, 215–218), Norton and Sommers assessed Black and White Americans’ perceptions of anti-Black and anti-White bias across the previous 6 decades—from the 1950s to the 2000s. They presented two key findings: White (but not Black) respondents perceived decreases in anti-Black bias to be associated with increases in anti-White bias, signaling the perception that racism is a zero-sum game; White respondents rated anti-White bias as more pronounced than anti-Black bias in the 2000s, signaling the perception that they were losing the zero-sum game. We collected new data to examine whether the key findings would be evident nearly a decade later and whether political ideology would moderate perceptions. Liberal, moderate, and conservative White (but not Black) Americans alike believed that racism is a zero-sum game. Liberal White Americans saw racism as a zero-sum game they were winning by a lot, moderate White Americans saw it as a game they were winning by only a little, and conservative White Americans saw it as a game they were losing. This work has clear implications for public policy and behavioral science and lays the groundwork for future research that examines to what extent racial differences in perceptions of racism by political ideology are changing over time.


Our results suggest that zero-sum thinking about racism pervades the entire political ideological spectrum among White Americans; even liberal White Americans believe that gains for Black people mean losses for White people. However, views of whether and by how much White people are seen as now winning or losing the zero-sum game vary by political ideology. Liberal, moderate, and conservative White Americans agree that White people were winning the zero-sum racism game in the past. They disagree on the outcome more recently; in the most recent decade, liberal White Americans see it as a game they are still winning by a lot, moderate White Americans see it as a game they are still winning but by a little, and conservative White Americans see racism as a zero-sum game they are now losing by a little.

Win or lose, why do White Americans, even liberal White Americans, view racism as a zero-sum game? The zero-sum pattern may be a logical consequence of structural racism, “racial practices that reproduce racial inequality in contemporary America [that] (1) are increasingly covert, (2) are embedded in normal operations of institutions, (3) avoid direct racial terminology, and (4) are invisible to most Whites” (Bonilla-Silva, 1997, p. 476). Racial progress by Black Americans may signal deviation from normal operations of American institutions, which is perceived as a threat to White Americans that motivates them to reassert cultural dominance (Wilkins et al., 2021).

Tuesday, August 23, 2022

Tackling Implicit Bias in Health Care

J. A. Sabin
N Engl J Med 2022; 387:105-107
DOI: 10.1056/NEJMp2201180

Implicit and explicit biases are among many factors that contribute to disparities in health and health care. Explicit biases, the attitudes and assumptions that we acknowledge as part of our personal belief systems, can be assessed directly by means of self-report. Explicit, overtly racist, sexist, and homophobic attitudes often underpin discriminatory actions. Implicit biases, by contrast, are attitudes and beliefs about race, ethnicity, age, ability, gender, or other characteristics that operate outside our conscious awareness and can be measured only indirectly. Implicit biases surreptitiously influence judgment and can, without intent, contribute to discriminatory behavior. A person can hold explicit egalitarian beliefs while harboring implicit attitudes and stereotypes that contradict their conscious beliefs.

Moreover, our individual biases operate within larger social, cultural, and economic structures whose biased policies and practices perpetuate systemic racism, sexism, and other forms of discrimination. In medicine, bias-driven discriminatory practices and policies not only negatively affect patient care and the medical training environment, but also limit the diversity of the health care workforce, lead to inequitable distribution of research funding, and can hinder career advancement.

A review of studies involving physicians, nurses, and other medical professionals found that health care providers’ implicit racial bias is associated with diagnostic uncertainty and, for Black patients, negative ratings of their clinical interactions, less patient-centeredness, poor provider communication, undertreatment of pain, views of Black patients as less medically adherent than White patients, and other ill effects.1 These biases are learned from cultural exposure and internalized over time: in one study, 48.7% of U.S. medical students surveyed reported having been exposed to negative comments about Black patients by attending or resident physicians, and those students demonstrated significantly greater implicit racial bias in year 4 than they had in year 1.

A review of the literature on reducing implicit bias, which examined evidence on many approaches and strategies, revealed that methods such as exposure to counterstereotypical exemplars, recognizing and understanding others’ perspectives, and appeals to egalitarian values have not resulted in reduction of implicit biases.2 Indeed, no interventions for reducing implicit biases have been shown to have enduring effects. Therefore, it makes sense for health care organizations to forgo bias-reduction interventions and focus instead on eliminating discriminatory behavior and other harms caused by implicit bias.

Though pervasive, implicit bias is hidden and difficult to recognize, especially in oneself. It can be assumed that we all hold implicit biases, but both individual and organizational actions can combat the harms caused by these attitudes and beliefs. Awareness of bias is one step toward behavior change. There are various ways to increase our awareness of personal biases, including taking the Harvard Implicit Association Tests, paying close attention to our own mistaken assumptions, and critically reflecting on biased behavior that we engage in or experience. Gonzalez and colleagues offer 12 tips for teaching recognition and management of implicit bias; these include creating a safe environment, presenting the science of implicit bias and evidence of its influence on clinical care, using critical reflection exercises, and engaging learners in skill-building exercises and activities in which they must embrace their discomfort.

Tuesday, June 7, 2022

Bigotry and the human–animal divide: (Dis)belief in human evolution and bigoted attitudes across different cultures

Syropoulos, S., Lifshin, U., et al. (2022). 
Journal of Personality and Social Psychology.
Advance online publication. 


The current investigation tested if people’s basic belief in the notion that human beings have developed from other animals (i.e., belief in evolution) can predict human-to-human prejudice and intergroup hostility. Using data from the American General Social Survey and Pew Research Center (Studies 1–4), and from three online samples (Studies 5, 7, 8) we tested this hypothesis across 45 countries, in diverse populations and religious settings, across time, in nationally representative data (N = 60,703), and with more comprehensive measures in online crowdsourced data (N = 2,846). Supporting the hypothesis, low belief in human evolution was associated with higher levels of prejudice, racist attitudes, and support for discriminatory behaviors against Lesbian, Gay, Bisexual, Transgender, and Queer (LGBTQ), Blacks, and immigrants in the United States (Study 1), with higher ingroup biases, prejudicial attitudes toward outgroups, and less support for conflict resolution in samples collected from 19 Eastern European countries (Study 2), 25 Muslim countries (Study 3), and Israel (Study 4). Further, among Americans, lower belief in evolution was associated with greater prejudice and militaristic attitudes toward political outgroups (Study 5). Finally, perceived similarity to animals (a construct distinct from belief in evolution, Study 6) partially mediated the link between belief in evolution and prejudice (Studies 7 and 8), even when controlling for religious beliefs, political views, and other demographic variables, and were also observed for nondominant groups (i.e., religious and racial minorities). Overall, these findings highlight the importance of belief in human evolution as a potentially key individual-difference variable predicting racism and prejudice.

General Discussion 

The current set of studies tested the hypothesis that believing that human beings evolved from animals, relates to (decreased) human-to-human prejudice and discrimination and negative attitudes towards various outgroups. In Study 1, we tested and found support for this hypothesis using data from the American GSS (Smith et al., 1972-2018). Across all the years in which a measure of belief in human evolution was included, it was consistently associated with less prejudice, less racist attitudes and decreased support for discriminatory behaviors against blacks and other minorities among white and presumably primarily heterosexual Americans. These results held when controlling for measures of religiosity, level of education and political views, and were not explained by other measures related to common knowledge, or attitudes towards animal rights (see Supplementary Materials). In Studies 2-4, we further tested if belief in human evolution predicted ingroup bias and negative attitudes towards outgroups in nationally representative samples of 45 countries obtained from the Pew Research Center, including data collected from Eastern Europe (19 countries), Muslim countries (25 countries), and Israel. In support of the hypothesis, belief in human evolution was mostly-consistently associated with decreased discrimination towards outgroups, a finding that held even after controlling for key demographic characteristics, such as religiosity and conservative political beliefs. In Study 4, Israelis who believe in human evolution were more likely to support a peaceful resolution to the Israeli-Palestinian conflict compared to those did not believe.

Monday, May 2, 2022

Mormon Leader Reaffirms Faith's Stance on Same-Sex Marriage

Sam Metz
Associated Press
Originally published 3 APR 22

A top leader in The Church of Jesus Christ of Latter-day Saints reaffirmed the faith’s opposition to same-sex marriage and “changes that confuse or alter gender” as debates over gender and sexuality reemerge throughout the United States.

Dallin H. Oaks, the second-highest-ranking leader of the faith known widely as the Mormon Church, told thousands of listeners gathered at a conference center at the church’s Salt Lake City headquarters that what he called “social and legal pressures” wouldn’t compel the church to alter its stances on same-sex marriage or matters of gender identity that he did not specify.

The highest level of salvation, Oaks said, “can only be attained through faithfulness to the covenants of an eternal marriage between a man and a woman. That divine doctrine is why we teach that gender is an essential characteristic of individual pre-mortal, mortal, and eternal identity and purpose.”

Oaks also said church doctrine “opposed changes that confuse or alter gender or homogenize the differences between men and women” and warned that “confusing gender, distorting marriage, and discouraging childbearing” was the devil’s work.

He also implored members of the faith to live peacefully and respect those with beliefs different than their own.

Oaks’ remarks reaffirm the faith’s long-held position on same-sex marriage that it has held to steadfastly even as its softened its policies on other LGTBQ matters, including allowing the children of same-sex couples to be baptized.

The Latter-day Saints’ reaffirmation of their stances comes as debates rage throughout the nation over transgender youth and what kids should learn about gender and sexuality. Officials in Texas have fought to classify gender confirmation surgeries as child abuse and Florida has outlawed instruction on sexual orientation and gender identity in kindergarten through third grade.

Sunday, March 6, 2022

Investigating the role of group-based morality in extreme behavioral expressions of prejudice

Hoover, J., Atari, M., et al. 
Nat Commun 12, 4585 (2021). 


Understanding motivations underlying acts of hatred are essential for developing strategies to prevent such extreme behavioral expressions of prejudice (EBEPs) against marginalized groups. In this work, we investigate the motivations underlying EBEPs as a function of moral values. Specifically, we propose EBEPs may often be best understood as morally motivated behaviors grounded in people’s moral values and perceptions of moral violations. As evidence, we report five studies that integrate spatial modeling and experimental methods to investigate the relationship between moral values and EBEPs. Our results, from these U.S. based studies, suggest that moral values oriented around group preservation are predictive of the county-level prevalence of hate groups and associated with the belief that extreme behavioral expressions of prejudice against marginalized groups are justified. Additional analyses suggest that the association between group-based moral values and EBEPs against outgroups can be partly explained by the belief that these groups have done something morally wrong.

From the Discussion

Notably, Study 5 provided tentative evidence that binding values may be a particularly important risk factor for the perceived justification of EBEPs. Participants who were experimentally manipulated to believe an outgroup had done something immoral were more likely to perceive acts of hate against that outgroup as justified when they felt that the outgroup’s behavior was more morally wrong. However, this association between PMW and the justification of hate acts was strongly moderated by people’s binding values, but not by their individualizing values. Ultimately, comparing people high on binding values to people high on individualizing values, we found that the average causal mediation effect in the domain of binding values was more than six times the average causal mediation effect in the domain of individualizing values. In other words, our results suggest that if two people see an outgroup’s binding values violation as equally morally wrong, but one of them has higher binding values, the person with higher binding values will see EBEPs against the outgroup as more justified. However, no such difference was observed in the domain of individualizing values.

Accordingly, our results suggest that people who attribute moral violations to an outgroup may be at higher risk for justifying, or perhaps even expressing, extreme prejudice toward outgroups; however, our results also suggest that people who prioritize the binding values may be particularly susceptible to this dynamic when they perceive a violation of ingroup loyalty, respect for authority, and physical or spiritual purity. In this sense, our findings are consistent with the hypothesis that acts of hate—a class of behaviors of which many have received their own special legal designation as particularly heinous crimes4—are partly motivated by individuals’ moral beliefs. This view is well-grounded in current understandings of the relationship between morality and acts of extremism or violence.

Wednesday, December 22, 2021

Dominant groups support digressive victimhood claims to counter accusations of discrimination

F. Danbold, et al.
Journal of Experimental Social Psychology
Volume 98, January 2022, 104233


When dominant groups are accused of discrimination against non-dominant groups, they often seek to portray themselves as the victims of discrimination instead. Sometimes, however, members of dominant groups counter accusations of discrimination by invoking victimhood on a new dimension of harm, changing the topic being discussed. Across three studies (N = 3081), we examine two examples of this digressive victimhood – Christian Americans responding to accusations of homophobia by claiming threatened religious liberty, and White Americans responding to accusations of racism by claiming threatened free speech. We show that members of dominant groups endorse digressive victimhood claims more strongly than conventional competitive victimhood claims (i.e., ones that claim “reverse discrimination”). Additionally, accounting for the fact that these claims may also stand to benefit a wider range of people and appeal to more abstract principles, we show that this preference is driven by the perception that digressive victimhood claims are more effective at silencing further criticism from the non-dominant group. Underscoring that these claims may be used strategically, we observed that individuals high in outgroup prejudice were willing to express a positive endorsement of the digressive victimhood claims even when they did not fully support the principle they claimed to be defending (e.g., freedom of religion or speech). We discuss implications for real-world intergroup conflicts and the psychology of dominant groups.


• Charged with discrimination, dominant groups often claim victimhood.

• These claims can be digressive, shifting the topic of conversation.

• Members of dominant groups prefer digressive claims over competitive claims.

• They see digressive claims as effective in silencing further criticism.

• Digressive victimhood claims are endorsed strategically and sometimes insincerely.

Wednesday, October 28, 2020

Small Victories: Texas social workers will no longer be allowed to discriminate against LGBTQ Texans and people with disabilities

Edgar Walters
Texas Tribune
Originally posted 27 Oct 20

After backlash from lawmakers and advocates, a state board voted Tuesday to undo a rule change that would have allowed social workers to turn away clients who are LGBTQ or have a disability.

The Texas Behavioral Health Executive Council voted unanimously to restore protections for LGBTQ and disabled clients to Texas social workers’ code of conduct just two weeks after removing them.

Gloria Canseco, who was appointed by Gov. Greg Abbott to lead the behavioral health council, expressed regret that the previous rule change was “perceived as hostile to the LGBTQ+ community or to disabled persons.”

“At every opportunity our intent is to prohibit discrimination against any person for any reason,” she said.

Abbott's office recommended earlier this month that the board strip three categories from a code of conduct that establishes when a social worker may refuse to serve someone.

Congratulations to all who help right a wrong in the mental health profession.

Saturday, October 17, 2020

New Texas rule lets social workers turn away clients who are LGBTQ or have a disability

Edgar Walters
Texas Tribune
Originally posted 14 Oct 2020

Texas social workers are criticizing a state regulatory board’s decision this week to remove protections for LGBTQ clients and clients with disabilities who seek social work services.

The Texas State Board of Social Work Examiners voted unanimously Monday to change a section of its code of conduct that establishes when a social worker may refuse to serve someone. The code will no longer prohibit social workers from turning away clients on the basis of disability, sexual orientation or gender identity.

Gov. Greg Abbott’s office recommended the change, board members said, because the code’s nondiscrimination protections went beyond protections laid out in the state law that governs how and when the state may discipline social workers.

“It’s not surprising that a board would align its rules with statutes passed by the Legislature,” said Abbott spokesperson Renae Eze. A state law passed last year gave the governor’s office more control over rules governing state-licensed professions.

The nondiscrimination policy change drew immediate criticism from a professional association. Will Francis, executive director of the Texas chapter of the National Association of Social Workers, called it “incredibly disheartening.”

He also criticized board members for removing the nondiscrimination protections without input from the social workers they license and oversee.

Note: All psychotherapy services are founded on the principle of beneficence: the desire to help others and do right by them.  This decision from the Texas State Board of Social Work Examiners is terrifyingly unethical.  The unanimous decision demonstrates the highest levels of incompetence and bigotry.

Sunday, March 15, 2020

Will Past Criminals Reoffend? (Humans are Terrible at Predicting; Algorithms Worse)

Sophie Bushwick
Scientific American
Originally published 14 Feb 2020

Here is an excerpt:

Based on the wider variety of experimental conditions, the new study concluded that algorithms such as COMPAS and LSI-R are indeed better than humans at predicting risk. This finding makes sense to Monahan, who emphasizes how difficult it is for people to make educated guesses about recidivism. “It’s not clear to me how, in real life situations—when actual judges are confronted with many, many things that could be risk factors and when they’re not given feedback—how the human judges could be as good as the statistical algorithms,” he says. But Goel cautions that his conclusion does not mean algorithms should be adopted unreservedly. “There are lots of open questions about the proper use of risk assessment in the criminal justice system,” he says. “I would hate for people to come away thinking, ‘Algorithms are better than humans. And so now we can all go home.’”

Goel points out that researchers are still studying how risk-assessment algorithms can encode racial biases. For instance, COMPAS can say whether a person might be arrested again—but one can be arrested without having committed an offense. “Rearrest for low-level crime is going to be dictated by where policing is occurring,” Goel says, “which itself is intensely concentrated in minority neighborhoods.” Researchers have been exploring the extent of bias in algorithms for years. Dressel and Farid also examined such issues in their 2018 paper. “Part of the problem with this idea that you're going to take the human out of [the] loop and remove the bias is: it’s ignoring the big, fat, whopping problem, which is the historical data is riddled with bias—against women, against people of color, against LGBTQ,” Farid says.

The info is here.

Friday, February 28, 2020

Lon Fuller and the Moral Value of the Rule of Law

Murphy, Colleen
Law and Philosophy,
Vol. 24, 2005.
Available at SSRN

It is often argued that the rule of law is only instrumentally morally valuable, valuable when and to the extent that a legal system is used to purse morally valuable ends. In this paper, I defend Lon Fuller’s view that the rule of law has conditional non-instrumental as well as instrumental moral value. I argue, along Fullerian lines, that the rule of law is conditionally non-instrumentally valuable in virtue of the way a legal system structures political relationships. The rule of law specifies a set of requirements which lawmakers must respect if they are to govern legally. As such, the rule of law restricts the illegal or extra-legal use of power. When a society rules by law, there are clear rules articulating the behavior appropriate for citizens and officials. Such rules ideally determine the particular contours political relationships will take. When the requirements of the rule of law are respected, the political relationships structured by the legal system constitutively express the moral values of reciprocity and respect for autonomy. The rule of law is instrumentally valuable, I argue, because in practice the rule of law limits the kind of injustice which governments pursue. There is in practice a deeper connection between ruling by law and the pursuit of moral ends than advocates
of the standard view recognize.

The next part of this paper outlines Lon Fuller’s conception of the rule of law and his explanation of its moral value. The third section illustrates how the Fullerian analysis draws attention to the impact that state-sanctioned atrocities can have upon the institutional functioning of the legal system, and so to their impact on the relationships between officials and citizens that are structured by that institution. The fourth section considers two objections to this account. According to the first, Razian objection, while the Fullerian analysis accurately describes the nature of the requirements of the rule of law, it offers a mistaken account of its moral value. Against my assertion that the rule of law has non-instrumental value, this objection argues that the rule of law is only instrumentally valuable. The second objection grants that the rule of law has non-instrumental moral value but claims that the Fullerian account of the requirements of the rule of law is incomplete.

Friday, December 6, 2019

The female problem: how male bias in medical trials ruined women's health

Gabrielle Jackson
The Guardian
Originally posted 13 Nov 19

Here is an excerpt:

The result of this male bias in research extends beyond clinical practice. Of the 10 prescription drugs taken off the market by the US Food and Drug Administration between 1997 and 2000 due to severe adverse effects, eight caused greater health risks in women. A 2018 study found this was a result of “serious male biases in basic, preclinical, and clinical research”.

The campaign had an effect in the US: in 1993, the FDA and the NIH mandated the inclusion of women in clinical trials. Between the 70s and 90s, these organisations and many other national and international regulators had a policy that ruled out women of so-called childbearing potential from early-stage drug trials.

The reasoning went like this: since women are born with all the eggs they will ever produce, they should be excluded from drug trials in case the drug proves toxic and impedes their ability to reproduce in the future.

The result was that all women were excluded from trials, regardless of their age, gender status, sexual orientation or wish or ability to bear children. Men, on the other hand, constantly reproduce their sperm, meaning they represent a reduced risk. It sounds like a sensible policy, except it treats all women like walking wombs and has introduced a huge bias into the health of the human race.

In their 1994 book Outrageous Practices, Leslie Laurence and Beth Weinhouse wrote: “It defies logic for researchers to acknowledge gender difference by claiming women’s hormones can affect study results – for instance, by affecting drug metabolism – but then to ignore these differences, study only men and extrapolate the results to women.”

The info is here.

Thursday, November 14, 2019

Assessing risk, automating racism

Embedded ImageRuha Benjamin
Science  25 Oct 2019:
Vol. 366, Issue 6464, pp. 421-422

Here is an excerpt:

Practically speaking, their finding means that if two people have the same risk score that indicates they do not need to be enrolled in a “high-risk management program,” the health of the Black patient is likely much worse than that of their White counterpart. According to Obermeyer et al., if the predictive tool were recalibrated to actual needs on the basis of the number and severity of active chronic illnesses, then twice as many Black patients would be identified for intervention. Notably, the researchers went well beyond the algorithm developers by constructing a more fine-grained measure of health outcomes, by extracting and cleaning data from electronic health records to determine the severity, not just the number, of conditions. Crucially, they found that so long as the tool remains effective at predicting costs, the outputs will continue to be racially biased by design, even as they may not explicitly attempt to take race into account. For this reason, Obermeyer et al. engage the literature on “problem formulation,” which illustrates that depending on how one defines the problem to be solved—whether to lower health care costs or to increase access to care—the outcomes will vary considerably.

Friday, September 6, 2019

Walking on Eggshells With Trainees in the Clinical Learning Environment—Avoiding the Eggshells Is Not the Answer.

Gold MA, Rosenthal SL, Wainberg ML.
JAMA Pediatr. 
Published online August 05, 2019.

Here is an excerpt:

Every trainee inevitably will encounter material or experiences that create discomfort. These situations are necessary for growth and faculty should be able to have the freedom in those situations to challenge the trainee’s assumptions.5 However, faculty have expressed concern that in the effort to manage the imbalance of power and protect trainees from the potential of abuse and harassment, we have labeled difficult conversations and discomfort as maltreatment. When faculty feel that the academic institution sides with trainees without considering the faculty member’s perspective and actions, they may feel as if their reputation and hard work as an educator has been challenged or ruined. For example, if a trainee reports a faculty member for creating a “sexually hostile” environment because the faculty has requested that the trainee take explicit sexual histories of adolescents, it may result in the faculty avoiding this type of difficult conversation and lead to a lack of skill development in trainees. Another unintended consequence is that trainees will not gain skills in having difficult conversations with their faculty, and without feedback they may not grow in their clinical expertise. As our workforce becomes increasingly diverse and we care for a range of populations, the likelihood of misunderstandings and the need to talk about sensitive topics and have difficult conversations increases.

There are several ways to create an environment that fosters the ability for trainees and faculty to walk across eggshells without fear. It is important to continue medical school training regarding unconscious bias, cultural sensitivity, and communication skills. This should include helping trainees not only apply these skills with each other and with their patients but also with their faculty. Trainees are likely to have as many unconscious biases toward their faculty as their faculty have toward them. For example, one study found that at one institution, female medical school faculty were given significantly lower teaching evaluations by third-year medical students in all clerkship rotations compared with male medical school faculty. Pediatrics showed the second largest difference, with surgery having the greatest difference.

The info is here.