scholarly journals Discrimination at School? When Stereotypes Affect Track Recommendations

2020 ◽  
Author(s):  
Sandra Gilgen
Keyword(s):  
Social Class ◽  
Educational Aspirations ◽  
School Achievement ◽  
Lower Class ◽  
Ordinary Least Squares ◽  
Statistical Discrimination ◽  
Least Squares Regression ◽  
Classroom Behaviour ◽  
The Hierarchical Structure ◽  
Minority Girls

This article examines whether teacher discrimination is an additional source of disadvantage for lower class and minority children, while also considering differential treatment by gender. Primary teachers in Bern, Switzerland, were asked to state the probabilities of recommending fictitious sixth graders – described in vignettes – to either the lower or higher track in secondary school. The factorial survey experiment, especially suited for addressing problems of social desirability bias, while enabling a direct measure of attitudes, included the dimensions: social class, minority status, gender, ability, motivation, classroom behaviour and parental educational aspirations. The results from the ordinary least squares regression models, accounting for the hierarchical structure (each respondent evaluated four vignettes so that N=216) with clustered standard errors, were mixed. While teachers lean towards treating ethnic minority girls favourably, they are significantly harsher on minority boys, compared to their Swiss counterparts. Throughout, teachers respond somewhat differently to girls and boys; sex-specific effects emerge for motivation, classroom behaviour and parental educational aspirations. In regard to social class, teachers tend towards a downward bias for lower class children in general, but it is yet again the boys that have a substantial disadvantage if they come from a lower class background. On the whole, the results indicate that discriminatory behaviour by teachers may indeed be one of the reasons for the lower school achievement of lower class and minority boys. While the theories of preference-based and statistical discrimination fail to account for the findings, the theory of statistical discrimination proves valuable in explaining the results.

Using a Rule Developing Experimentation Approach to Study Social Problems

2019 ◽  
Vol 6 (3) ◽  
pp. 23-48 ◽  
Author(s):  
Attila Gere ◽  
Petraq Papajorgji ◽  
Howard R. Moskowitz ◽  
Veljko Milutinovic
Keyword(s):  
Data Mining ◽  
Social Class ◽  
Least Squares ◽  
Regression Models ◽  
Negative Emotion ◽  
Ordinary Least Squares ◽  
Least Squares Regression ◽  
Online Experiment ◽  
Data Mining Techniques ◽  
The Usa

This article presents the first in a series of studies on the corruption of various types, assessed through an online experiment known as mind genomics. The data allows for the creation of simple models from regression, showing the part-worth contribution of every element to perceived corruption, and to perceived positive, neutral or negative emotion. The authors use ordinary least squares regression models and advanced data mining techniques to analyze the data and classify the users accordingly. They present the results from four countries (Albania, Hungary, India, and the USA), looking at the linkages between corruption by country, and by other factors such as social class. Based on the collected data a model is generated for each group (country, type of person), showing how the person in the group is likely to call a description ‘corrupt,' and how each particular element from the set of 20 elements related to education adds or subtracts to that basic proclivity to call a situation or behavior corrupt.

scholarly journals Least Likely Observations in Regression Models for Categorical Outcomes

2002 ◽  
Vol 2 (3) ◽  
pp. 296-300 ◽  
Author(s):  
Jeremy Freese
Keyword(s):  
Logistic Regression ◽  
Regression Models ◽  
Binary Logistic Regression ◽  
Positive Outcome ◽  
Ordinary Least Squares ◽  
Parameter Estimates ◽  
Least Squares Regression ◽  
Binary Logistic Regression Model ◽  
Ordered Logistic Regression ◽  
Negative Outcome

This article presents a method and program for identifying poorly fitting observations for maximum-likelihood regression models for categorical dependent variables. After estimating a model, the program leastlikely will list the observations that have the lowest predicted probabilities of observing the value of the outcome category that was actually observed. For example, when run after estimating a binary logistic regression model, leastlikely will list the observations with a positive outcome that had the lowest predicted probabilities of a positive outcome and the observations with a negative outcome that had the lowest predicted probabilities of a negative outcome. These can be considered the observations in which the outcome is most surprising given the values of the independent variables and the parameter estimates and, like observations with large residuals in ordinary least squares regression, may warrant individual inspection. Use of the program is illustrated with examples using binary and ordered logistic regression.

Family Livelihood, Social Class and Mothers’ Self-cognition: The Transformation of “Mothering” in Japanese Colonial Taiwan (1895–1945)

2020 ◽  
pp. 036319902094573
Author(s):  
Yujen Chen
Keyword(s):  
Social Class ◽  
Lower Class ◽  
Household Tasks ◽  
New Women ◽  
Biological Mothers ◽  
Professional Careers ◽  
Taiwanese Women ◽  
Women's Lives ◽  
Japanese Colonial ◽  
Physical Care

Based on oral histories and diaries of women who lived in the Japanese colonial period, this article analyzes the role and transformation of “mothering” in Taiwan, examining how the Han Chinese patriarchal society in Taiwan responded to colonialization and modernization in the early twentieth century. It reveals that most Taiwanese women at that time married in their teens and began to take on the tasks of mothers before the age of twenty. Difference in social class served as a key element affecting mothering practices. Rural and lower-class mothers had no choice but to prioritize productive labor over physical childcare; women of the traditional upper class could afford nannies; the emerging group of “new women” hired lower-class women to help with household tasks and childcare while they developed their professional careers. In addition to the physical care of children, Taiwanese mothers put great emphasis on the education and future development of children, especially sons. However, as the custom of “daughters-in-law-to-be” was quite common, from an early age many girls faced only their “mothers-in-law-to-be” instead of their biological mothers. “Mothering” was thus absent in these women’s lives, complicating the meaning of “motherhood.”

Home Health Agencies: Empirical Evidence on the Patient-Driven Groupings Model’s Expected Effects on Agency Reimbursements

2021 ◽  
pp. 108482232199038
Author(s):  
Elizabeth Plummer ◽  
William F. Wempe
Keyword(s):  
Ordinary Least Squares ◽  
Process Quality ◽  
Home Health ◽  
Least Squares Regression ◽  
Residual Variation ◽  
Health Agencies ◽  
Dual Eligible ◽  
Home Health Agencies ◽  
Seriously Ill Patients ◽  
Seriously Ill

Beginning January 1, 2020, Medicare’s Patient-Driven Groupings Model (PDGM) eliminated therapy as a direct determinant of Home Health Agencies’ (HHAs’) reimbursements. Instead, PDGM advances Medicare’s shift toward value-based payment models by directly linking HHAs’ reimbursements to patients’ medical conditions. We use 3 publicly-available datasets and ordered logistic regression to examine the associations between HHAs’ pre-PDGM provision of therapy and their other agency, patient, and quality characteristics. Our study therefore provides evidence on PDGM’s likely effects on HHA reimbursements assuming current patient populations and service levels do not change. We find that PDGM will likely increase payments to rural and facility-based HHAs, as well as HHAs serving greater proportions of non-white, dual-eligible, and seriously ill patients. Payments will also increase for HHAs scoring higher on quality surveys, but decrease for HHAs with higher outcome and process quality scores. We also use ordinary least squares regression to examine residual variation in HHAs’ expected reimbursement changes under PDGM, after accounting for any expected changes related to their pre-PDGM levels of therapy provision. We find that larger and rural HHAs will likely experience residual payment increases under PDGM, as will HHAs with greater numbers of seriously ill, younger, and non-white patients. HHAs with higher process quality, but lower outcome quality, will similarly benefit from PDGM. Understanding how PDGM affects HHAs is crucial as policymakers seek ways to increase equitable access to safe and affordable non-facility-provided healthcare that provides appropriate levels of therapy, nursing, and other care.

scholarly journals Predicting presenteeism using measures of health status

2021 ◽  
Author(s):  
Cheryl Jones ◽  
Katherine Payne ◽  
Alexander Thompson ◽  
Suzanne M. M. Verstappen
Keyword(s):  
Health Status ◽  
Online Survey ◽  
Activity Index ◽  
Work Productivity ◽  
Rank Correlation ◽  
Ordinary Least Squares ◽  
Statistical Correlation ◽  
Least Squares Regression ◽  
Mapping Algorithm ◽  
Spearman’S Rank Correlation

Abstract Objectives To identify whether it is feasible to develop a mapping algorithm to predict presenteeism using multiattribute measures of health status. Methods Data were collected using a bespoke online survey in a purposive sample (n = 472) of working individuals with a self-reported diagnosis of Rheumatoid arthritis (RA). Survey respondents were recruited using an online panel company (ResearchNow). This study used data captured using two multiattribute measures of health status (EQ5D-5 level; SF6D) and a measure of presenteeism (WPAI, Work Productivity Activity Index). Statistical correlation between the WPAI and the two measures of health status (EQ5D-5 level; SF6D) was assessed using Spearman’s rank correlation. Five regression models were estimated to quantify the relationship between WPAI and predict presenteeism using health status. The models were specified based in index and domain scores and included covariates (age; gender). Estimated and observed presenteeism were compared using tenfold cross-validation and evaluated using Root mean square error (RMSE). Results A strong and negative correlation was found between WPAI and: EQ5D-5 level and WPAI (r = − 0.64); SF6D (r =− 0.60). Two models, using ordinary least squares regression were identified as the best performing models specifying health status using: SF6D domains with age interacted with gender (RMSE = 1.7858); EQ5D-5 Level domains and age interacted with gender (RMSE = 1.7859). Conclusions This study provides indicative evidence that two existing measures of health status (SF6D and EQ5D-5L) have a quantifiable relationship with a measure of presenteeism (WPAI) for an exemplar application of working individuals with RA. A future study should assess the external validity of the proposed mapping algorithms.

From Measures of Association to Multilevel Models: Sociology Journals and the Quantitative Literacy Gap

2020 ◽  
pp. 0092055X2098042
Author(s):  
Thomas J. Linneman
Keyword(s):  
Multilevel Models ◽  
Ordinary Least Squares ◽  
Quantitative Literacy ◽  
Least Squares Regression ◽  
Journal Articles ◽  
Measures Of Association ◽  
Chi Square ◽  
Literacy Gap ◽  
Statistics Course ◽  
Sociology Journals

While most sociology majors must take a statistics course, the content of this course varies widely across departments. Starting from the assumption that sociology students should be able to engage effectively with the sociological literature, this article examines the statistical techniques used in 2,804 journal articles—from four generalist sociology journals from 1990 to 2019 and 11 additional sociology journals from 2019—in order to assess which techniques have risen or fallen in prevalence. Although stalwarts such as ordinary least squares regression, chi-square tests, and t tests maintain strong presences, the rise of logistic regression, interaction effects, and multilevel models has been dramatic. After assessing the proportion of articles students hypothetically could understand given various levels of statistical training, the article ends with suggestions for how to revamp the statistics course to help our students become more numerate citizens, both in their sociology courses and in the world at large.

Open But Segregated? Class Divisions And the Network Structure of Social Capital in Chile

Social Forces ◽  
2021 ◽  
Author(s):  
Gabriel Otero ◽  
Beate Volker ◽  
Jesper Rozer
Keyword(s):  
Social Capital ◽  
Social Class ◽  
Large Scale ◽  
Lower Class ◽  
Social Resources ◽  
Economic Capital ◽  
Economic Disadvantage ◽  
Occupational Class ◽  
Class Divisions ◽  
Heterogeneous Class

Abstract This paper studies how social capital is divided across classes in Chile, one of the most unequal countries in the world. We analyse the extent to which upper-, middle-, and lower class individuals congregate in social networks with similar others, while following Bourdieu and expecting that in particular the networks of the higher social strata are segregated in terms of social capital. We test our argument with large-scale, representative survey data for the Chilean urban population aged 18–75 years (n = 2,517) and build an integrated indicator of people’s social class that combines measures of education, occupational class, and household income. Our regression analyses show that upper-class individuals have larger networks and access to more varied and prestigious social resources than their middle- and lower class counterparts. Interestingly, however, we found a U-shaped relationship between social class and class homogeneity, indicating that network segregation is high at the top as well as at the bottom of the class-based social strata. In contrast, the classes in the middle have more heterogeneous class networks, possibly forming an important bridge between the “edges” of the class structure. These findings demonstrate that whereas social and economic capital cumulates in higher classes, the lower classes are socially deprived next to their economic disadvantage.

scholarly journals Lack of Informations about COVID-19 Vaccine: From Implications to Intervention for Supporting Public Health Communications in COVID-19 Pandemic

2021 ◽  
Vol 18 (11) ◽  
pp. 6141
Author(s):  
Silva Guljaš ◽  
Zvonimir Bosnić ◽  
Tamer Salha ◽  
Monika Berecki ◽  
Zdravka Krivdić Dupan ◽  
...  
Keyword(s):  
Vaccine Efficacy ◽  
Health Belief ◽  
Ordinary Least Squares ◽  
Vaccine Hesitancy ◽  
Equal Proportion ◽  
Least Squares Regression ◽  
Online Questionnaire ◽  
Demographic Groups ◽  
Population Immunity ◽  
Wide Range

Lack of knowledge and mistrust towards vaccines represent a challenge in achieving the vaccination coverage required for population immunity. The aim of this study is to examine the opinion that specific demographic groups have about COVID-19 vaccination, in order to detect potential fears and reasons for negative attitudes towards vaccination, and to gain knowledge on how to prepare strategies to eliminate possible misinformation that could affect vaccine hesitancy. The data collection approach was based on online questionnaire surveys, divided into three groups of questions that followed the main postulates of the health belief theory—a theory that helps understanding a behaviour of the public in some concrete surrounding in receiving preventive measures. Ordinary least squares regression analyses were used to examine the influence of individual factors on refusing the vaccine, and to provide information on the perception of participants on the danger of COVID-19 infection, and on potential barriers that could retard the vaccine utility. There was an equal proportion of participants (total number 276) who planned on receiving the COVID-19 vaccine (37%), and of those who did not (36.3%). The rest (26.7%) of participants were still indecisive. Our results indicated that attitudes on whether to receive the vaccine, on how serious consequences might be if getting the infection, as well as a suspicious towards the vaccine efficacy and the fear of the vaccine potential side effects, may depend on participants’ age (<40 vs. >40 years) and on whether they are healthcare workers or not. The barriers that make participants‘ unsure about of receiving the vaccine, such as a distrust in the vaccine efficacy and safety, may vary in different socio-demographic groups and depending on which is the point of time in the course of the pandemic development, as well as on the vaccine availability and experience in using certain vaccine formulas. There is a pressing need for health services to continuously provide information to the general population, and to address the root causes of mistrust through improved communication, using a wide range of policies, interventions and technologies.

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