John A Curiel
Biographic Data
| ID | 4180165 |
|---|---|
| NAME | John A Curiel |
| GIVEN NAMES | John A |
| FAMILY NAME | Curiel |
| SIGNATURE | CURIEL J A |
| AFFILIATIONS | Ohio Northern University |
| ORCID | 0000-0002-4399-8582 |
| VERIFIED | Yes |
| TOTAL WORKS | 7 |
| TOTAL CITATIONS | 11 |
| WORKS AS AUTHOR | 7 |
| WORKS AS EDITOR | 0 |
| FIRST PUBLICATION YEAR | 2022 |
| LATEST PUBLICATION YEAR | 2025 |
| H-INDEX | 2 |
Automating Identification of Toxic Comments in Student Evaluations of Teaching
The Power of Characters
Identifying racial disparities in policy and politics is a pressing area of research within the United States. Where early work made use of identifying potentially noisy correlations between county or precinct demographics and election outcomes, the advent of Bayesian Improved Surname Geocoding (BISG) vastly improved estimation of race by employing voter lists. Machine Learning (ML)-modified BISG in turn offers accuracy gains over the static – an…
The Accuracy of Identifying Constituencies with Geographic Assignment Within State Legislative Districts
Identifying the geographic constituencies of representatives is among the most crucial, yet challenging, aspects of state and local politics research. Regularly changing district lines, incomplete data, and computational obstacles can present barriers to matching individuals to their respective districts. Geocoding residential addresses is the ideal method for matching purposes. However, cost constraints can limit its applicability for many resea…
Validating the Applicability of Bayesian Inference with Surname and Geocoding to Congressional Redistricting
Ensuring descriptive representation of racial minorities without packing minorities too heavily into districts is a perpetual difficulty, especially in states lacking voter file race data. One advance since the 2010 redistricting cycle is the advent of Bayesian Improved Surname Geocoding (BISG), which greatly improves upon previous ecological inference methods in identifying voter race. In this article, we test the viability of employing BISG to …
Redistricting Out Descriptive Representation
Redistricting poses a potential harm to American voters in limiting choice and accountability at the polls. Although voters still retain their right to contact their representatives, research shows that the confusion created when redistricting divides ZIP codes confounds the constituent–representative link. We build on existing research that shows splitting ZIP codes across multiple congressional districts leads to harms in representation. Specif…
Minmaxing of Bayesian Improved Surname Geocoding and Geography Level Ups in Predicting Race
Racial identification is a critical factor in understanding a multitude of important outcomes in many fields. However, inferring an individual’s race from ecological data is prone to bias and error. This process was only recently improved via Bayesian improved surname geocoding (BISG). With surname and geographic-based demographic data, it is possible to more accurately estimate individual racial identification than ever before. However, the leve…
Mainstream Media Recirculation of Trust-Reducing Social Media Messages
Citizens need to trust in the integrity of news reporting for the free press to fulfill its role as a democratic institution that enables citizens to hold representatives accountable. Growing research has shown that increased use of social media erodes trust in legacy news. However, trust-reducing social media messages are not contained to social media platforms; they are widely recirculated by the mainstream media. We argue that mainstream media…
Minmaxing of Bayesian Improved Surname Geocoding and Geography Level Ups in Predicting Race
Racial identification is a critical factor in understanding a multitude of important outcomes in many fields. However, inferring an individual’s race from ecological data is prone to bias and error. This process was only recently improved via Bayesian improved surname geocoding (BISG). With surname and geographic-based demographic data, it is possible to more accurately estimate individual racial identification than ever before. However, the leve…
Validating the Applicability of Bayesian Inference with Surname and Geocoding to Congressional Redistricting
Ensuring descriptive representation of racial minorities without packing minorities too heavily into districts is a perpetual difficulty, especially in states lacking voter file race data. One advance since the 2010 redistricting cycle is the advent of Bayesian Improved Surname Geocoding (BISG), which greatly improves upon previous ecological inference methods in identifying voter race. In this article, we test the viability of employing BISG to …
The Accuracy of Identifying Constituencies with Geographic Assignment Within State Legislative Districts
Identifying the geographic constituencies of representatives is among the most crucial, yet challenging, aspects of state and local politics research. Regularly changing district lines, incomplete data, and computational obstacles can present barriers to matching individuals to their respective districts. Geocoding residential addresses is the ideal method for matching purposes. However, cost constraints can limit its applicability for many resea…
Mainstream Media Recirculation of Trust-Reducing Social Media Messages
Citizens need to trust in the integrity of news reporting for the free press to fulfill its role as a democratic institution that enables citizens to hold representatives accountable. Growing research has shown that increased use of social media erodes trust in legacy news. However, trust-reducing social media messages are not contained to social media platforms; they are widely recirculated by the mainstream media. We argue that mainstream media…
Redistricting Out Descriptive Representation
Redistricting poses a potential harm to American voters in limiting choice and accountability at the polls. Although voters still retain their right to contact their representatives, research shows that the confusion created when redistricting divides ZIP codes confounds the constituent–representative link. We build on existing research that shows splitting ZIP codes across multiple congressional districts leads to harms in representation. Specif…
Minmaxing of Bayesian Improved Surname Geocoding and Geography Level Ups in Predicting Race
Racial identification is a critical factor in understanding a multitude of important outcomes in many fields. However, inferring an individual’s race from ecological data is prone to bias and error. This process was only recently improved via Bayesian improved surname geocoding (BISG). With surname and geographic-based demographic data, it is possible to more accurately estimate individual racial identification than ever before. However, the leve…
Mainstream Media Recirculation of Trust-Reducing Social Media Messages
Citizens need to trust in the integrity of news reporting for the free press to fulfill its role as a democratic institution that enables citizens to hold representatives accountable. Growing research has shown that increased use of social media erodes trust in legacy news. However, trust-reducing social media messages are not contained to social media platforms; they are widely recirculated by the mainstream media. We argue that mainstream media…
The Accuracy of Identifying Constituencies with Geographic Assignment Within State Legislative Districts
Identifying the geographic constituencies of representatives is among the most crucial, yet challenging, aspects of state and local politics research. Regularly changing district lines, incomplete data, and computational obstacles can present barriers to matching individuals to their respective districts. Geocoding residential addresses is the ideal method for matching purposes. However, cost constraints can limit its applicability for many resea…
Validating the Applicability of Bayesian Inference with Surname and Geocoding to Congressional Redistricting
Ensuring descriptive representation of racial minorities without packing minorities too heavily into districts is a perpetual difficulty, especially in states lacking voter file race data. One advance since the 2010 redistricting cycle is the advent of Bayesian Improved Surname Geocoding (BISG), which greatly improves upon previous ecological inference methods in identifying voter race. In this article, we test the viability of employing BISG to …
The Power of Characters
Identifying racial disparities in policy and politics is a pressing area of research within the United States. Where early work made use of identifying potentially noisy correlations between county or precinct demographics and election outcomes, the advent of Bayesian Improved Surname Geocoding (BISG) vastly improved estimation of race by employing voter lists. Machine Learning (ML)-modified BISG in turn offers accuracy gains over the static – an…
Automating Identification of Toxic Comments in Student Evaluations of Teaching
Computer Science (6 works) · Law (5 works) · Political science (5 works) · Artificial Intelligence (4 works) · Cartography (4 works) · Geocoding (4 works) · Geography (4 works) · Mathematics (4 works) · Politics (4 works) · Sociology (4 works)