Barbara Kiviat
Biographic Data
| ID | 295704 |
|---|---|
| NAME | Barbara Kiviat |
| GIVEN NAMES | Barbara |
| FAMILY NAME | Kiviat |
| SIGNATURE | KIVIAT B |
| AFFILIATIONS | Stanford University, Stanford, CA, USA |
| ORCID | 0000-0002-2142-5871 |
| VERIFIED | Yes |
| TOTAL WORKS | 10 |
| TOTAL CITATIONS | 225 |
| AUTHOR COUNT | 10 |
| EDITOR COUNT | 0 |
| FIRST PUBLICATION YEAR | 2012 |
| LATEST PUBLICATION YEAR | 2026 |
| H-INDEX | 6 |
Seeing Like a Company or a Customer: Selective Empathy in Pricing
Sociologists have long shown that moral beliefs are key to sustaining market arrangements. Yet surprisingly little research has examined how groups may assess the fairness of taken-for-granted market practices differently. In this article, we draw on three survey studies to examine Americans’ moral beliefs about risk-based pricing, a pricing institution in which consumers who are predicted to be costly are charged more. In markets for both insura…
Exceptions in the Algorithmic Age: Evidence from the Case of Tenant Screening
International audience
The Moral Affordances of Construing People as Cases: How Algorithms and the Data They Depend on Obscure Narrative and Noncomparative Justice
Like many modes of rationalized governance, algorithms depend on rendering people as cases: discrete entities defined by regularized, atemporal attributes. This enables the computation behind the behavioral predictions organizations increasingly use to allocate benefits and burdens. Yet it elides another foundational way of understanding people: as actors in the unfolding narratives of their lives. This has epistemic implications because each cul…
Deciding between Domains: How Borrowers Weigh Market and Interpersonal Options
Individuals routinely satisfy borrowing needs by transacting in the market or by relying on social relations. In the market domain, price logic leads borrowers to choose the cheaper option; in the interpersonal domain, role-matching logic leads borrowers to choose the relation best matched to the act. But how do individuals choose when faced with options from each domain? Drawing on theories in economic sociology that assert the economic and the …
Which Data Fairly Differentiate? American Views on the Use of Personal Data in Two Market Settings
Corporations increasingly use personal data to offer individuals different products and prices. I present first-of-its-kind evidence about how U.S. consumers assess the fairness of companies using personal information in this way. Drawing on a nationally representative survey that asks respondents to rate how fair or unfair it is for car insurers and lenders to use various sorts of information—from credit scores to web browser history to resident…
The Moral Limits of Predictive Practices: The Case of Credit-Based Insurance Scores
Corporations gather massive amounts of personal data to predict how individuals will behave so that they can profitably price goods and allocate resources. This article investigates the moral foundations of such increasingly prevalent market practices. I leverage the case of credit scores in car insurance pricing-an early and controversial use of algorithmic prediction in the U.S. consumer economy-to unpack the premise that predictive data are fa…
Disparate Impact? Race, Sex, and Credit Reports in Hiring
Half of U.S. employers consider credit history when deciding whom to hire. The practice has become a contentious policy issue, with multiple jurisdictions limiting the use of credit reports in employment. Yet to date, there has been no test of how the introduction of credit history influences the way employers make decisions. Recent qualitative research finds that employers evaluate credit reports in contingent and person-specific ways, which ope…
The art of deciding with data: Evidence From How Employers Translate Credit Reports Into Hiring Decisions
About half of US employers consider personal credit history when hiring, a practice that connects individuals' prospects for employment to their financial pasts. Yet little is known about how employers translate credit reports, complicated financial documents, into hiring decisions. Using interviews with 57 hiring professionals, this paper offers the first in-depth look at how employers move from document to decision. Faced with the context-free …
Forced Relocation and Residential Instability among Urban Renters
Residential instability often brings about other forms of instability in families, schools, and communities that compromise the life chances of adults and children. Social scientists have found that low-income families move frequently without fully understanding why. Drawing on novel data of more than 1,000 Milwaukee renters, this article explores the relationship between forced relocation and residential instability. It finds that low incomes ar…
The Invention of Thrift: How Government Got People to Save
Forced Relocation and Residential Instability among Urban Renters
Residential instability often brings about other forms of instability in families, schools, and communities that compromise the life chances of adults and children. Social scientists have found that low-income families move frequently without fully understanding why. Drawing on novel data of more than 1,000 Milwaukee renters, this article explores the relationship between forced relocation and residential instability. It finds that low incomes ar…
The Moral Limits of Predictive Practices: The Case of Credit-Based Insurance Scores
Corporations gather massive amounts of personal data to predict how individuals will behave so that they can profitably price goods and allocate resources. This article investigates the moral foundations of such increasingly prevalent market practices. I leverage the case of credit scores in car insurance pricing-an early and controversial use of algorithmic prediction in the U.S. consumer economy-to unpack the premise that predictive data are fa…
The art of deciding with data: Evidence From How Employers Translate Credit Reports Into Hiring Decisions
About half of US employers consider personal credit history when hiring, a practice that connects individuals' prospects for employment to their financial pasts. Yet little is known about how employers translate credit reports, complicated financial documents, into hiring decisions. Using interviews with 57 hiring professionals, this paper offers the first in-depth look at how employers move from document to decision. Faced with the context-free …
Disparate Impact? Race, Sex, and Credit Reports in Hiring
Half of U.S. employers consider credit history when deciding whom to hire. The practice has become a contentious policy issue, with multiple jurisdictions limiting the use of credit reports in employment. Yet to date, there has been no test of how the introduction of credit history influences the way employers make decisions. Recent qualitative research finds that employers evaluate credit reports in contingent and person-specific ways, which ope…
The Moral Affordances of Construing People as Cases: How Algorithms and the Data They Depend on Obscure Narrative and Noncomparative Justice
Like many modes of rationalized governance, algorithms depend on rendering people as cases: discrete entities defined by regularized, atemporal attributes. This enables the computation behind the behavioral predictions organizations increasingly use to allocate benefits and burdens. Yet it elides another foundational way of understanding people: as actors in the unfolding narratives of their lives. This has epistemic implications because each cul…
Deciding between Domains: How Borrowers Weigh Market and Interpersonal Options
Individuals routinely satisfy borrowing needs by transacting in the market or by relying on social relations. In the market domain, price logic leads borrowers to choose the cheaper option; in the interpersonal domain, role-matching logic leads borrowers to choose the relation best matched to the act. But how do individuals choose when faced with options from each domain? Drawing on theories in economic sociology that assert the economic and the …
Which Data Fairly Differentiate? American Views on the Use of Personal Data in Two Market Settings
Corporations increasingly use personal data to offer individuals different products and prices. I present first-of-its-kind evidence about how U.S. consumers assess the fairness of companies using personal information in this way. Drawing on a nationally representative survey that asks respondents to rate how fair or unfair it is for car insurers and lenders to use various sorts of information—from credit scores to web browser history to resident…
The Invention of Thrift: How Government Got People to Save
Forced Relocation and Residential Instability among Urban Renters
Residential instability often brings about other forms of instability in families, schools, and communities that compromise the life chances of adults and children. Social scientists have found that low-income families move frequently without fully understanding why. Drawing on novel data of more than 1,000 Milwaukee renters, this article explores the relationship between forced relocation and residential instability. It finds that low incomes ar…
The art of deciding with data: Evidence From How Employers Translate Credit Reports Into Hiring Decisions
About half of US employers consider personal credit history when hiring, a practice that connects individuals' prospects for employment to their financial pasts. Yet little is known about how employers translate credit reports, complicated financial documents, into hiring decisions. Using interviews with 57 hiring professionals, this paper offers the first in-depth look at how employers move from document to decision. Faced with the context-free …
Disparate Impact? Race, Sex, and Credit Reports in Hiring
Half of U.S. employers consider credit history when deciding whom to hire. The practice has become a contentious policy issue, with multiple jurisdictions limiting the use of credit reports in employment. Yet to date, there has been no test of how the introduction of credit history influences the way employers make decisions. Recent qualitative research finds that employers evaluate credit reports in contingent and person-specific ways, which ope…
The Moral Limits of Predictive Practices: The Case of Credit-Based Insurance Scores
Corporations gather massive amounts of personal data to predict how individuals will behave so that they can profitably price goods and allocate resources. This article investigates the moral foundations of such increasingly prevalent market practices. I leverage the case of credit scores in car insurance pricing-an early and controversial use of algorithmic prediction in the U.S. consumer economy-to unpack the premise that predictive data are fa…
Which Data Fairly Differentiate? American Views on the Use of Personal Data in Two Market Settings
Corporations increasingly use personal data to offer individuals different products and prices. I present first-of-its-kind evidence about how U.S. consumers assess the fairness of companies using personal information in this way. Drawing on a nationally representative survey that asks respondents to rate how fair or unfair it is for car insurers and lenders to use various sorts of information—from credit scores to web browser history to resident…
Deciding between Domains: How Borrowers Weigh Market and Interpersonal Options
Individuals routinely satisfy borrowing needs by transacting in the market or by relying on social relations. In the market domain, price logic leads borrowers to choose the cheaper option; in the interpersonal domain, role-matching logic leads borrowers to choose the relation best matched to the act. But how do individuals choose when faced with options from each domain? Drawing on theories in economic sociology that assert the economic and the …
The Moral Affordances of Construing People as Cases: How Algorithms and the Data They Depend on Obscure Narrative and Noncomparative Justice
Like many modes of rationalized governance, algorithms depend on rendering people as cases: discrete entities defined by regularized, atemporal attributes. This enables the computation behind the behavioral predictions organizations increasingly use to allocate benefits and burdens. Yet it elides another foundational way of understanding people: as actors in the unfolding narratives of their lives. This has epistemic implications because each cul…
Exceptions in the Algorithmic Age: Evidence from the Case of Tenant Screening
International audience
Seeing Like a Company or a Customer: Selective Empathy in Pricing
Sociologists have long shown that moral beliefs are key to sustaining market arrangements. Yet surprisingly little research has examined how groups may assess the fairness of taken-for-granted market practices differently. In this article, we draw on three survey studies to examine Americans’ moral beliefs about risk-based pricing, a pricing institution in which consumers who are predicted to be costly are charged more. In markets for both insura…
Political science (7 works) · Law (6 works) · Law (6 works) · Actuarial science (5 works) · Economics (5 works) · Business (4 works) · Sociology (4 works) · Computer Science (3 works) · Finance (3 works) · Management and Organizational Studies (3 works)