Social Science Survey Research Articles

Exploring the Influence of Internet Usage Attitudes on Educational Equity among Chinese Migrant Workers: A Regional Analysis

As urban builders, migrant workers (rural residents working in cities) should fairly enjoy urban educational resources. However, due to their social status, they face numerous educational challenges. This study explores how Chinese migrant workers' attitudes towards Internet usage influence educational equity, particularly in an environment where the Internet has become indispensable for learning, work, and daily life among Chinese residents. Using ANOVA and correlation analysis, the study investigates the relationship and influencing factors between migrant workers' attitudes towards Internet usage and educational equity. The research data were obtained from a 2020 survey conducted by the Peking University Chinese Social Sciences Survey Center, focusing primarily on Chinese migrant workers. The findings reveal that migrant workers' attitudes towards Internet usage significantly impact educational equity; groups that place greater emphasis on Internet usage exhibit better educational equity than others. Although the statistical differences in Internet usage attitudes among different regions are not significant, educational equity disparities among regions remain statistically significant. Based on these findings, recommendations are provided at the family, school, and government levels, aiming to address the digital divide, establish remote open education platforms, and improve the household registration system to enhance educational equity for migrant workers.

Enhancing FAIR compliance: A controlled vocabulary for mapping Social Sciences survey variables

Enhancing FAIR compliance: A controlled vocabulary for mapping Social Sciences survey variables

A dataset on survey designs and quality of social and behavioral science surveys during the COVID-19 pandemic

In the social and behavioral sciences, surveys are frequently used to collect data. During the COVID-19 pandemic, surveys provided political actors and public health professionals with timely insights on the attitudes and behaviors of the general population. These insights were key in guiding actions to fight the pandemic. However, the data quality of these surveys remains unclear because systematic knowledge about how the survey data were collected during the COVID-19 pandemic is lacking. This is unfortunate, since decades of survey research have shown that survey design impacts data. Our Survey Data Collection and the COVID-19 Pandemic (SDCCP) project deals with this research gap. We collected rich metadata on survey design for 717 social and behavioral science surveys carried out in Germany during the first two years of the COVID-19 pandemic. In this data descriptor, we present a unique resource for a systematic assessment of the survey data collection practices and quality of surveys conducted in Germany during the COVID-19 pandemic.

The ‘Implicit Intelligence’ of artificial intelligence. Investigating the potential of large language models in social science research

ABSTRACT Researchers in ‘hard' science disciplines are exploring the transformative potential of Artificial Intelligence (AI) for advancing research in their fields. Their colleagues in ‘soft' science, however, have produced thus far a limited number of articles on this subject. This paper addresses this gap. Our main hypothesis is that existing Artificial Intelligence Large Language Models (LLMs) can closely align with human expert assessments in specialized social science surveys. To test this, we compare data from a multi-country expert survey with those collected from the two powerful LLMs created by OpenAI and Google. The statistical difference between the two sets of data is minimal in most cases, supporting our hypothesis, albeit with certain limitations and within specific parameters. The tested language models demonstrate domain-agnostic algorithmic accuracy, indicating an inherent ability to incorporate human knowledge and independently replicate human judgment across various subfields without specific training. We refer to this property as the ‘implicit intelligence' of Artificial Intelligence, representing a highly promising advancement for social science research.

Influence of Female Educational Level on Consumption of Family Education

As education becomes more and more important, more and more families pay attention to education, and the proportion of education consumption in family consumption is increasing. According to the data of the Seventh National Census Bulletin, with the popularization of basic education, women 's level of education is increasing. This study uses the Chinese Family Tracking Survey completed by the Chinese Social Science Survey Center of Peking University in 2020. The aim of this study was to investigate the effect of female educational level on family education consumption by means of linear regression. It is concluded that there is a significant positive correlation between female education level and family education consumption. It suggests that the higher the level of education for women, the higher the consumption of family education, and the level of education for women has an increasing impact on the level of consumption of family education. The education level of women has become an important factor affecting the consumption of family education.

Cultural capital, the digital divide, and the health of older adults: a moderated mediation effect test

BackgroundIt is of great practical significance to study the intrinsic relationship between cultural capital, digital divide, cognitive ability, and health of older adults in the dual social context of population aging and the digital era.MethodsWe analyzed data from the 2020 China Family Panel Studies (CFPS) initiated by the China Center for Social Science Surveys at Peking University. Physical health, mental health, and memory health were set as indicators of older adults, and the relationship between cultural capital, digital divide, cognitive ability, and health of older adults was examined by hierarchical regression with moderated mediated effect methods.ResultsImprovement in the health of older adults is associated with an increase in the level of cultural capital; cultural capital may bridge the digital divide faced by older adults, which in turn promotes the improvement of the health of older adults; the higher the level of cognitive ability, the stronger the effect of cultural capital on the digital divide, and at the same time, the stronger the mediating effect of the digital divide; cultural capital has a more pronounced effect on the health of older male adults living in the city.ConclusionsThe results of the study show that cultural capital can have a positive impact on the health of older adults, but there is urban-rural heterogeneity and gender heterogeneity, in which the digital divide plays a mediating role, and the enhancement of the cognitive ability of older adults will be conducive to the improvement of their health, so the health of older adults should be promoted by improving the level of their cultural capital and the ability of older adults to use digital technology, thus provide references for the protection of health of older adults.

Methodological considerations and assumptions in social science survey research

The articles in this special issue are based largely on results from online social surveys on beliefs and self-reported behaviours related to COVID-19, with an emphasis on ethnicity differences. There are many considerations and assumptions used when conducting this type of research, and when analysing the resulting data, which are often not discussed in the resulting journal articles. These include how the research questions are chosen, how the measurement of the key constructs is done and the analytic approach. The article goes through several of the steps necessary to conduct social science survey research that are often not reported in papers. The aim is to provide a backstage view of how this approach to social scientific questions occurs, pulling back the curtain on these issues.

On the efficiency of modified regression-type mean imputation scheme under two-phase sampling

Human-based surveys such as medical and social science surveys are often characterized by non-response or missing observations. In this study, a new class of regression-type mean imputation method that uses X̄n as an estimate of X̄ was suggested. Using partial derivative approach, the MSEs of the class of estimators presented were derived up to first order approximation under two cases. Case I: when the secondary sample S2 of size n(n<n1) is a subset of preliminary sample S1[S2 ⸦ S1] , and Case II: is when secondary sample S2 is a subset of universal set ΩN . Conditions for which the new estimator was more efficient than the other estimators studied were derived. The results of numerical examples through simulations revealed that the suggested class of estimators is more efficient.

Great Lakes for whom? Community outcomes in the Muskegon Lake and White Lake areas of concern

We use social science survey methods to evaluate the extent to which residents in Great Lakes Areas of Concern (AOC) experience social gaps in accessing benefits of AOC restorations, comparing post-restoration outcomes in two AOCs with differing socioeconomic profiles in Muskegon County, Michigan: Muskegon Lake and White Lake. We find that survey respondents engage in similar types of recreational activities with similar rates of frequency across sites, but Muskegon residents have more pessimistic perceptions of the environmental and community outcomes of the Muskegon Lake restoration. On closer inspection, significant differences in post-restoration assessments exist within the City of Muskegon, with residents from neighborhoods where environmental (in)justice risk factors are high reporting continuing concerns about environmental quality and social problems. We highlight the relevance of these observations to community redevelopment in Great Lakes AOCs that share Muskegon’s historic context and present-day demographic profile, pointing to a potential for equity gaps that require conscientious planning.

Research anomalies in criminology: How serious? How extensive over time? And who was responsible?

ABSTRACT A variety of ways to detect questionable research practices in small sample social science surveys have been discussed by a variety of authors. However, some of those approaches (e.g., GRIM test, SPRITE test) do not work well for results obtained from larger samples. Here several approaches for detecting anomalies in larger samples are presented and illustrated by an analysis of 78 journal articles in the area of criminology, 59 by Dr. Eric Stewart, published since 1998 with similar methods and/or authors. Of all 59 articles, 28 (47.5%, p < .001, d = 0.94) had two or more major anomalies compared to none of the 19 control group articles. It was also found that the larger the role of Dr. Stewart in article authorship, the greater the number of anomalies detected (p < .001, d = 1.01) while for his coauthors, there were few significant relationships between their roles and total anomalies. Our results demonstrate that extensive problematic results can remain undetected for decades despite several levels of peer review and other scientific controls; however, use of two types of control groups and the use of statistical methods for measuring and evaluating anomalies can improve detection.

Examining how internet use and non-farm employment affect rural households’ income gap? Evidence from China

The objective of this study is to assess the effect of Internet use on the income disparity between rural households and to determine how Internet usage can be used to reduce this income gap. We use the Recentered Influence Function Regression (RIF) and data from the China Family Panel Studies (CFPS) conducted by the China Social Science Survey (CSSS) center at Peking University to make the results of regression estimation more reliable. The results reveal that Internet use can make rural households’ income gap shrink considerably, and that the degree of non-farm employment among rural families has a mediating effect between Internet use and the income disparity of farm households. In addition, the Eastern region experiences a stronger mitigating effect from Internet use, whereas ethnic minorities find out no such mitigating effect. This study expands the scope of income disparity theory, provides new ideas for the construction of digital villages, and identifies new empirical evidence and decision-making grounds for improving the livelihoods of rural households and narrowing the income gap between rural households.

Operation Simulation and Economic Analysis of Household Hybrid PV and BESS Systems in the Improved TOU Mode

With the popularization of electric vehicles and electric boilers, household electricity consumption will increase significantly. Household hybrid photovoltaic (PV) systems and battery energy storage systems (BESSs) can supply increasing household electricity consumption without expanding the existing distribution network. This paper validates the technical feasibility of connecting a large number of household power users that contain BESSs and PVs in a distribution line by a simulation in Matlab. In addition to technical feasibility, this article improves the time-of-use (TOU) form to achieve economic feasibility (covering equipment costs). In the past, the TOU was set from the perspective of the load demand of the grid, but the actual user participation would affect this effect. In this paper, based on a social science survey, a new three-level rate TOU is introduced, which has little impact on residents’ lifestyle, to effectively increase the response frequency effectively. Combined with the improved TOU and the state of PVs, the BESS control mode is set for simulation. To compare the three-tier rate TOU with the normal TOU tariff and select the best household BESS size, a MATLAB simulation is used to simulate the common household BESS capacity. The results indicate that the combination of the three-tier rate TOU with a 4 kWh household BESS can afford the investment of household PVs and BESSs. The high cost issue that previously primarily limited the true use of BESSs is expected to be resolved.

Social and moral psychology of COVID-19 across 69 countries

The COVID-19 pandemic has affected all domains of human life, including the economic and social fabric of societies. One of the central strategies for managing public health throughout the pandemic has been through persuasive messaging and collective behaviour change. To help scholars better understand the social and moral psychology behind public health behaviour, we present a dataset comprising of 51,404 individuals from 69 countries. This dataset was collected for the International Collaboration on Social & Moral Psychology of COVID-19 project (ICSMP COVID-19). This social science survey invited participants around the world to complete a series of moral and psychological measures and public health attitudes about COVID-19 during an early phase of the COVID-19 pandemic (between April and June 2020). The survey included seven broad categories of questions: COVID-19 beliefs and compliance behaviours; identity and social attitudes; ideology; health and well-being; moral beliefs and motivation; personality traits; and demographic variables. We report both raw and cleaned data, along with all survey materials, data visualisations, and psychometric evaluations of key variables.

Evaluating Traffic Operation Conditions during Wildfire Evacuation Using Connected Vehicles Data

With climate change and the resulting rise in temperatures, wildfire risk is increasing all over the world, particularly in the Western United States. Communities in wildland–urban interface (WUI) areas are at the greatest risk of fire. Such fires cause mass evacuations and can result in traffic congestion, endangering the lives of both citizens and first responders. While existing wildfire evacuation research focuses on social science surveys and fire spread modeling, they lack data on traffic operations during such incidents. Additionally, traditional traffic data collection methods are unable to gather large sets of data on historical wildfire events. However, the recent availability of connected vehicle (CV) data containing lane-level precision historical vehicle movement data has enabled researchers to assess traffic operational performance at the region and timeframe of interest. To address this gap, this study utilized a CV dataset to analyze traffic operations during a short-notice evacuation event caused by a wildfire, demonstrating that the CV dataset is an effective tool for accurately assessing traffic delays and overall traffic operation conditions during the selected fire incident. The findings also showed that the selected CV dataset provides high temporal coverage and similar travel time estimates as compared to an alternate method of travel time estimation. The study thus emphasized the importance of utilizing advanced technologies, such as CV data, to develop effective evacuation strategies and improve emergency management.

The determinants of the mobility patterns of the elderly in Switzerland

Like most industrialized countries, Switzerland is characterized by an aging population. However, it differentiates itself from other countries because of its low home-ownership rate. Also, the lack of specialized housing for the elderly encourages them to stay in their current accommodation instead of moving to a smaller place thereby vacating space for family housing. Given this challenge, it is important for governments as well as other housing providers to understand better the needs of the elderly with respect to their housing situation and their patterns of mobility. Accordingly, our research aims to identify the key determinants that trigger the intention, on the part of the elderly in Switzerland, to move. For this purpose, we use secondary data obtained from the Swiss Household Panel, which is a longitudinal social sciences survey which annually interviews a random sample of private households in Switzerland using computer-assisted interviewing. We focus on respondents aged 60 and older over the period from 2013 to 2018, and our sample includes 13 313 observations. We investigate the role of intentions to move as a function of socio-demographic factors, health and life events, dwelling characteristics as well as satisfaction factors. By exploring the importance of these elements on the intention to move within a logistic regression model framework, we confirm the findings of recent studies including those that affirm that the willingness to move decreases with age, and that the elderly do not adapt the size of their home for a smaller dwelling. In addition, while we find no evidence for the impact of dwelling characteristics and health or life events, we provide empirical evidence for socio-demographic and satisfaction factors that influence the intention to move. From our results, we observe that not being satisfied with the accommodation, living in the German-speaking region of Switzerland, judging the accommodation to be too large, and being a tenant, all increase the intention to move. Our findings contribute to the welfare of the elderly in Switzerland by helping governments as well as private entities to plan housing adapted to their needs better.

Can Retracted Social Science Articles Be Distinguished from Non-Retracted Articles by Some of the Same Authors, Using Benford’s Law or Other Statistical Methods?

A variety of ways to detect problems in small sample social science surveys has been discussed by a variety of authors. Here, several new approaches for detecting anomalies in large samples are presented and their use illustrated through comparisons of seven retracted or corrected journal articles with a control group of eight articles published since 2000 by a similar group of authors on similar topics; all the articles involved samples from several hundred to many thousands of participants. Given the small sample of articles (k = 15) and low statistical power, only 2/12 of individual anomaly comparisons were not statistically significant, but large effect sizes (d &gt; 0.80) were common for most of the anomaly comparisons. A six-item total anomaly scale featured a Cronbach alpha of 0.92, suggesting that the six anomalies were moderately correlated rather than isolated issues. The total anomaly scale differentiated the two groups of articles, with an effect size of 3.55 (p &lt; 0.001); an anomaly severity scale derived from the same six items, with an alpha of 0.94, yielded an effect size of 3.52 (p &lt; 0.001). Deviations from the predicted distribution of first digits in regression coefficients (Benford’s Law) were associated with anomalies and differences between the two groups of articles; however, the results were mixed in terms of statistical significance, though the effect sizes were large (d ≥ 0.90). The methodology was able to detect unusual anomalies in both retracted and non-retracted articles. In conclusion, the results provide several useful approaches that may be helpful for detecting questionable research practices, especially data or results fabrication, in social science, medical, or other scientific research.

:The Masses Are Revolting: Victorian Culture and the Aesthetics of Disgust

:<i>The Masses Are Revolting: Victorian Culture and the Aesthetics of Disgust</i>

Prevalence of malocclusions in 8- and 9-year-old children in Germany-Results of the Sixth German Oral Health Study (DMS6).

Current population-wide data on the prevalence of malocclusions in 8‑ and 9‑year-old children in Germany are not available. Therefore, the primary objective of this study was to collect data on the prevalence of malocclusions in 8‑ and 9‑year-old children in Germany. The secondary objective of this study was to use this information to derive the need for orthodontic care provision. This is an oral-epidemiological investigation and social science survey at the national level with afocus on tooth and jaw misalignment. The investigation took place between January and March 2021 at 16study centers across Germany. All relevant data were available for the 705study participants and were included in the statistical analysis. Overbite was the most common finding with 88.9%. Also widespread were crowding, with at least 60.9%, and lack of space, with ashare of 30.9%. All other indication groups had ashare below 10%. Rare (< 1%) were buccal and lingual occlusions and craniofacial abnormalities. The most severe forms of disease (Orthodontic Indication Group [Kieferorthopädische Indikationsgruppen, KIG] grade5) were overbite (3.2%), open bite malocclusion (1.0%), undershot (0.6%), and craniofacial abnormalities (0.4%). The proportion of study participants who required orthodontic treatment, in accordance with statutory health insurance provider guidelines, was 40.4%. The proportion of study participants in principle requiring orthodontic treatment for medical reasons was 97.5%. Systemic differences in the need for orthodontic care provision relating to gender, region, or social status were not identified. In general, the need for care provision identified in the orthodontic indication groups corresponds to that shown in previous studies. This suggests that the need for orthodontic treatment in Germany has remained stable over the years.

Methodology of the Sixth German Oral Health Study (DMS6) to survey tooth and jaw misalignment.

The aim of this study was (1)to complete and update the oral-epidemiological data situation in Germany (descriptive epidemiology) and (2)to determine the need for orthodontic treatment provision based on the epidemiological data situation (health care epidemiology in the form of demand research). For this purpose, alongitudinal oral-epidemiological study and social science survey with aprimary focus on tooth and jaw misalignment was conducted at anationally representative level on 705 8‑ and 9‑year-old children across Germany. The methodological principles of the oral-epidemiological study are described, with afocus on the calibration and reliability assessment results from the study dentists, sample weighting, asurvey of nonrespondents to estimate the extent of the external validity of the study results, adescription of the study participants, and realized cases, as well as information pertaining to the response rate and utilization. Based on the conducted analyses, it can be assumed that the examined 8‑ and 9‑year-old study participants are representative of the statistical population in Germany.

The choice of response alternatives in COVID-19 social science surveys.

Social science research is key for understanding and for predicting compliance with COVID-19 guidelines, and this research relies on survey data. While much focus is on the survey question stems, less is on the response alternatives presented that both constrain responses and convey information about the assumed expectations of the survey designers. The focus here is on the choice of response alternatives for the types of behavioral frequency questions used in many COVID-19 and other health surveys. We examine issues with two types of response alternatives. The first are vague quantifiers, like "rarely" and "frequently." Using data from 30 countries from the Imperial COVID data hub, we show that the interpretation of these vague quantifiers (and their translations) depends on the norms in that country. If the mean amount of hand washing in a country is high, it is likely "frequently" corresponds to a higher numeric value for hand washing than if the mean in the country is low. The second type are sets of numeric alternatives and they can also be problematic. Using a US survey, respondents were randomly allocated to receive either response alternatives where most of the scale corresponds to low frequencies or where most of the scale corresponds to high frequencies. Those given the low frequency set provided lower estimates of the health behaviors. The choice of response alternatives for behavioral frequency questions can affect the estimates of health behaviors. How the response alternatives mold the responses should be taken into account for epidemiological modeling. We conclude with some recommendations for response alternatives for behavioral frequency questions in surveys.