scholarly journals Integrating Human and Machine Coding to Measure Political Issues in Ethnic Newspaper Articles

2020 ◽  
Author(s):  
Jae Yeon Kim
Keyword(s):  
African American ◽  
Asian American ◽  
Large Scale ◽  
Minority Groups ◽  
State Violence ◽  
Training Data ◽  
Political Issues ◽  
Classification Framework ◽  
The 1960S ◽  
Automated Text Classification

The voices of racial minority groups have rarely been examined systematically with large-scale text analysis in political science. This study fills such a gap by applying an integrated classification framework to the analysis of the commonalities and differences in political issues that appeared in 78,305 articles from Asian American and African American newspapers from the 1960s to the 1980s. The automated text classification shows that Asian American newspapers focused on promoting collective gains more often than African American newspapers. Conversely, African American newspapers concentrated on preventing collective losses more than Asian American newspapers. The content analysis demonstrates that the issue priorities varied between the corpora, especially with respect to policy contexts. Gaining access to government resources was a more urgent issue for Asian Americans, while reducing or ending state violence, such as police brutality, was a more pressing matter for African Americans. It also helped avoid extreme interpretations of the machine coding, as the misalignment of political agendas between the two corpora widened up to 10 times when the training data were measured using the minimum, rather than the maximum, reliability threshold.

Does the Tea Party Really Want Their Country Back?

2014 ◽  
Author(s):  
Christopher S. Parker ◽  
Matt A. Barreto
Keyword(s):  
African American ◽  
Civil Rights ◽  
Ethnic Minorities ◽  
Asian American ◽  
American History ◽  
Minority Groups ◽  
Equal Treatment ◽  
Tea Party ◽  
Equal Rights ◽  
Racial Ethnic

This chapter analyzes claims made by the Tea Party's critics, who argue that the movement is one rooted in bigotry. The minority and immigrant population in America has grown dramatically, eventually leading to the election of many prominent African American, Latino, and Asian American candidates to office. At the same time, minority groups have continued to promote equal rights, especially civil rights for a range of groups, including racial/ethnic minorities, women, and sexual minorities. Yet, American history is filled with periods during which increasing visibility and calls for equal treatment among out-groups has been repeatedly met with opposition from dominant groups. The chapter calls into question whether or not Tea Party supporters see all Americans as equal members of society entitled to the same access to the American dream.

The Racialization of the African-American and Asian-American Citizen: A Comparative Legal Analysis

2019 ◽  
Vol 3 ◽  
pp. 30-41
Author(s):  
Mallory Yung
Keyword(s):  
African American ◽  
Asian Americans ◽  
Asian American ◽  
Model Minority ◽  
Legal Discourse ◽  
Court Cases ◽  
Legal Analysis ◽  
Critical Race ◽  
Social Hierarchies ◽  
American Citizen

The perception of racial tensions in North American settler countries has historically been focused on the Black/White relationship, as has much of the theoretical legal discourse surrounding the concept of “race”. Accordingly, the scope of much critical race scholarship has been restricted such that it rarely acknowledges the racial tensions that persist between different racially-excluded minorities. This paper hopes to expand and integrate the examination of Black and Asian-American racialization that critical race scholars have previously revealed. It will do this by historicizing the respective contours of Black and Asian-American racialization processes through legislation and landmark court cases in a neo-colonial context. The defining features of racialization which have culminated in the ultimate divergence of each group’s racialization will be compared and contrasted. This divergence sees the differential labeling of Asian-Americans as the ‘model minority’ while Blacks continue to be subjugated by modern modalities of exclusionary systems of control. The consequences of this divergence in relation to preserving existing racial and social hierarchies will be discussed in the final sections of this paper.

DeepSSPred: A Deep Learning Based Sulfenylation site predictor via a novel n-segmented optimize federated feature encoder

2020 ◽  
Vol 27 ◽  
Author(s):  
Zaheer Ullah Khan ◽  
Dechang Pi
Keyword(s):  
Large Scale ◽  
Computational Models ◽  
Research Work ◽  
Training Data ◽  
Training Dataset ◽  
Validation Dataset ◽  
Cytokine Signaling ◽  
Minority Class ◽  
Independent Dataset ◽  
Feature Encoding

Background: S-sulfenylation (S-sulphenylation, or sulfenic acid) proteins, are special kinds of post-translation modification, which plays an important role in various physiological and pathological processes such as cytokine signaling, transcriptional regulation, and apoptosis. Despite these aforementioned significances, and by complementing existing wet methods, several computational models have been developed for sulfenylation cysteine sites prediction. However, the performance of these models was not satisfactory due to inefficient feature schemes, severe imbalance issues, and lack of an intelligent learning engine. Objective: In this study, our motivation is to establish a strong and novel computational predictor for discrimination of sulfenylation and non-sulfenylation sites. Methods: In this study, we report an innovative bioinformatics feature encoding tool, named DeepSSPred, in which, resulting encoded features is obtained via n-segmented hybrid feature, and then the resampling technique called synthetic minority oversampling was employed to cope with the severe imbalance issue between SC-sites (minority class) and non-SC sites (majority class). State of the art 2DConvolutional Neural Network was employed over rigorous 10-fold jackknife cross-validation technique for model validation and authentication. Results: Following the proposed framework, with a strong discrete presentation of feature space, machine learning engine, and unbiased presentation of the underline training data yielded into an excellent model that outperforms with all existing established studies. The proposed approach is 6% higher in terms of MCC from the first best. On an independent dataset, the existing first best study failed to provide sufficient details. The model obtained an increase of 7.5% in accuracy, 1.22% in Sn, 12.91% in Sp and 13.12% in MCC on the training data and12.13% of ACC, 27.25% in Sn, 2.25% in Sp, and 30.37% in MCC on an independent dataset in comparison with 2nd best method. These empirical analyses show the superlative performance of the proposed model over both training and Independent dataset in comparison with existing literature studies. Conclusion : In this research, we have developed a novel sequence-based automated predictor for SC-sites, called DeepSSPred. The empirical simulations outcomes with a training dataset and independent validation dataset have revealed the efficacy of the proposed theoretical model. The good performance of DeepSSPred is due to several reasons, such as novel discriminative feature encoding schemes, SMOTE technique, and careful construction of the prediction model through the tuned 2D-CNN classifier. We believe that our research work will provide a potential insight into a further prediction of S-sulfenylation characteristics and functionalities. Thus, we hope that our developed predictor will significantly helpful for large scale discrimination of unknown SC-sites in particular and designing new pharmaceutical drugs in general.

African and African American Religions in the Early Americas

2018 ◽  
Author(s):  
Jason Young
Keyword(s):  
African American ◽  
Belief Systems ◽  
Subsequent Development ◽  
Religious Practices ◽  
African American Religion ◽  
African Religion ◽  
1960S And 1970S ◽  
The 1960S ◽  
New Generation ◽  
The Relationship

This chapter chronicles the relationship between African religious practices on the continent and African American religion in the plantation Americas in the era of slavery and the transatlantic slave trade. A new generation of scholars who emerged in the 1960s and 1970s have demonstrated not only that African religious practices exhibit remarkable subtlety and complexity but also that these cultures have played significant roles in the subsequent development of religious practices throughout the world. Christianity, Islam, and traditional African religion comprised a set of broad and varied religious practices that contributed to the development of creative, subtle, and complex belief systems that circulated around the African Diaspora. In addition, this chapter addresses some of the vexed epistemological challenges related to discussing and describing non-Western ritual and religious practices.

Concrete Monsters of the Welfare State: Discussions of Brutalist Architecture on Social Media

2021 ◽  
pp. 120633122110193
Author(s):  
Max Holleran
Keyword(s):  
Social Media ◽  
Welfare State ◽  
Large Scale ◽  
Eastern European ◽  
Municipal Governments ◽  
Online Social Media ◽  
1960S And 1970S ◽  
The 1960S ◽  
The Aesthetic ◽  
The Welfare State

Brutalist architecture is an object of fascination on social media that has taken on new popularity in recent years. This article, drawing on 3,000 social media posts in Russian and English, argues that the buildings stand out for their arresting scale and their association with the expanding state in the 1960s and 1970s. In both North Atlantic and Eastern European contexts, the aesthetic was employed in publicly financed urban planning projects, creating imposing concrete structures for universities, libraries, and government offices. While some online social media users associate the style with the overreach of both socialist and capitalist governments, others are more nostalgic. They use Brutalist buildings as a means to start conversations about welfare state goals of social housing, free university, and other services. They also lament that many municipal governments no longer have the capacity or vision to take on large-scale projects of reworking the built environment to meet contemporary challenges.

Knowledge Transfer with Weighted Adversarial Network for Cold-Start Store Site Recommendation

2021 ◽  
Vol 15 (3) ◽  
pp. 1-27
Author(s):  
Yan Liu ◽  
Bin Guo ◽  
Daqing Zhang ◽  
Djamal Zeghlache ◽  
Jingmin Chen ◽  
...  
Keyword(s):  
Large Scale ◽  
Cold Start ◽  
Weighting Scheme ◽  
Training Data ◽  
Chain Store ◽  
Useful Knowledge ◽  
Adversarial Network ◽  
Brick And Mortar ◽  
New City ◽  
Learning Machine

Store site recommendation aims to predict the value of the store at candidate locations and then recommend the optimal location to the company for placing a new brick-and-mortar store. Most existing studies focus on learning machine learning or deep learning models based on large-scale training data of existing chain stores in the same city. However, the expansion of chain enterprises in new cities suffers from data scarcity issues, and these models do not work in the new city where no chain store has been placed (i.e., cold-start problem). In this article, we propose a unified approach for cold-start store site recommendation, Weighted Adversarial Network with Transferability weighting scheme (WANT), to transfer knowledge learned from a data-rich source city to a target city with no labeled data. In particular, to promote positive transfer, we develop a discriminator to diminish distribution discrepancy between source city and target city with different data distributions, which plays the minimax game with the feature extractor to learn transferable representations across cities by adversarial learning. In addition, to further reduce the risk of negative transfer, we design a transferability weighting scheme to quantify the transferability of examples in source city and reweight the contribution of relevant source examples to transfer useful knowledge. We validate WANT using a real-world dataset, and experimental results demonstrate the effectiveness of our proposed model over several state-of-the-art baseline models.

scholarly journals How Other Minorities Gained Access: The War on Poverty and Asian American and Latino Community Organizing

2020 ◽  
pp. 106591292098345
Author(s):  
Jae Yeon Kim
Keyword(s):  
Asian Americans ◽  
Asian American ◽  
Community Organizing ◽  
War On Poverty ◽  
Advocacy Organizations ◽  
Minority Community ◽  
Original Dataset ◽  
Community Organizers ◽  
1960S And 1970S ◽  
The 1960S

In the early twentieth century, Asian Americans and Latinos organized along national origin lines and focused on assimilation; By the 1960s and 1970s, community organizers from both groups began to form panethnic community service organizations (CSOs) that emphasized solidarity. I argue that focusing on the rise of panethnic CSOs reveals an underappreciated mechanism that has mobilized Asian Americans and Latinos—the welfare state. The War on Poverty programs incentivized non-black minority community organizers to form panethnic CSOs to gain access to state resources and serve the economically disadvantaged in their communities. Drawing on extensive archival research, I identify this mechanism and test it with my original dataset of 818 Asian American and Latino advocacy organizations and CSOs. Leveraging the Reagan budget cut, I show that dismantling the War on Poverty programs reduced the founding rate of panethnic CSOs. I further estimated that a 1 percent increase in federal funding was associated with the increase of the two panethnic CSOs during the War on Poverty. The findings demonstrate how access to state resources forces activists among non-primary beneficiary groups to build new political identities that fit the dominant image of the policy beneficiaries.

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