scholarly journals Bayesian Hierarchical Models for Measuring Varietal Improvement in Tobacco Yield and Quality

2021 ◽  
pp. 1-24
Author(s):  
A. Ford Ramsey ◽  
Roderick M. Rejesus
Keyword(s):  
Hierarchical Models ◽  
The United States ◽  
Limited Data ◽  
Bayesian Hierarchical ◽  
Minimum Standards ◽  
Yield And Quality ◽  
Acceptable Quality ◽  
Quality Dimensions ◽  
Varietal Improvement ◽  
Quality Constraint

Abstract We measure the economic impact of varietal improvement and technological change in flue-cured tobacco across quantity (e.g., yield) and quality dimensions under a voluntary quality constraint. Since 1961, flue-cured tobacco breeders in the United States have been subject to the Minimum Standards Program that sets limits on acceptable quality characteristics for commercial tobacco varieties. We implement a Bayesian hierarchical model to measure the contribution of breeding efforts to changes in tobacco yields and quality between 1954 and 2017. The Bayesian model addresses limited data for varieties in the trials and allows easy generation of the necessary parameters of economic interest.

Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

2008 ◽  
Author(s):  
Ralph F. Milliff ◽  
Mark Berliner ◽  
Emanuele D. Lorenzo ◽  
Christopher K. Wikle
Keyword(s):  
Hierarchical Models ◽  
Bayesian Hierarchical Models ◽  
Forecast System ◽  
Bayesian Hierarchical ◽  
The Mediterranean

Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

2010 ◽  
Author(s):  
Christopher K. Wikle ◽  
L. M. Berliner ◽  
Emanuele Di Lorenzo ◽  
Ralph F. Milliff
Keyword(s):  
Hierarchical Models ◽  
Bayesian Hierarchical Models ◽  
Forecast System ◽  
Bayesian Hierarchical ◽  
The Mediterranean

Bayesian Hierarchical Models to Augment the Mediterranean Forecast System

2010 ◽  
Author(s):  
Ralph F. Milliff ◽  
Christopher K. Wikle ◽  
L. M. Berliner ◽  
Emanuele Di Lorenzo
Keyword(s):  
Hierarchical Models ◽  
Bayesian Hierarchical Models ◽  
Forecast System ◽  
Bayesian Hierarchical ◽  
The Mediterranean

Researching American Muslims: A Case Study of Surveillance and Racialized State Control

2021 ◽  
pp. 1-16
Author(s):  
Hajer Al-Faham
Keyword(s):  
United States ◽  
Science Research ◽  
The United States ◽  
State Control ◽  
Limited Data ◽  
American Muslims ◽  
State Repression ◽  
Second Stage ◽  
Selection Of

How does surveillance shape political science research in the United States? In comparative and international politics, there is a rich literature concerning the conduct of research amid conditions of conflict and state repression. As this literature locates “the field” in distant contexts “over there,” the United States continues to be saturated with various forms of state control. What this portends for American politics research has thus far been examined by a limited selection of scholars. Expanding on their insights, I situate “the field” in the United States and examine surveillance of American Muslims, an understudied case of racialized state control. Drawing on qualitative data from a case study of sixty-nine interviews with Arab and Black American Muslims, I argue that surveillance operated as a two-stage political mechanism that mapped onto research methodologically and substantively. In the first stage, surveillance reconfigured the researcher-researchee dynamic, hindered recruitment and access, and limited data-collection. In the second stage, surveillance colored the self-perceptions, political attitudes, and civic engagement of respondents, thereby indicating a political socialization unfolding among Muslims. The implications of this study suggest that researchers can mitigate against some, but not all, of the challenges presented by surveillance and concomitant forms of state control.

Identifying and intercepting health misinformation on Reddit dermatology forums with artificially intelligent bots using natural language processing (Preprint)

2021 ◽  
Author(s):  
Monique B. Sager ◽  
Aditya M. Kashyap ◽  
Mila Tamminga ◽  
Sadhana Ravoori ◽  
Christopher Callison-Burch ◽  
...  
Keyword(s):  
Natural Language Processing ◽  
Natural Language ◽  
Language Processing ◽  
The United States ◽  
Test Accuracy ◽  
Limited Data ◽  
Test Environment ◽  
Data Set ◽  
Inappropriate Care ◽  
Processing Techniques

BACKGROUND Reddit, the fifth most popular website in the United States, boasts a large and engaged user base on its dermatology forums where users crowdsource free medical opinions. Unfortunately, much of the advice provided is unvalidated and could lead to inappropriate care. Initial testing has shown that artificially intelligent bots can detect misinformation on Reddit forums and may be able to produce responses to posts containing misinformation. OBJECTIVE To analyze the ability of bots to find and respond to health misinformation on Reddit’s dermatology forums in a controlled test environment. METHODS Using natural language processing techniques, we trained bots to target misinformation using relevant keywords and to post pre-fabricated responses. By evaluating different model architectures across a held-out test set, we compared performances. RESULTS Our models yielded data test accuracies ranging from 95%-100%, with a BERT fine-tuned model resulting in the highest level of test accuracy. Bots were then able to post corrective pre-fabricated responses to misinformation. CONCLUSIONS Using a limited data set, bots had near-perfect ability to detect these examples of health misinformation within Reddit dermatology forums. Given that these bots can then post pre-fabricated responses, this technique may allow for interception of misinformation. Providing correct information, even instantly, however, does not mean users will be receptive or find such interventions persuasive. Further work should investigate this strategy’s effectiveness to inform future deployment of bots as a technique in combating health misinformation. CLINICALTRIAL N/A

Sign in / Sign up

Export Citation Format

Share Document