Social Science Questions Research Articles

Broadening ecological footprint and biocapacity research: A co-developed research agenda with Canadian stakeholders

The Ecological Footprint and Biocapacity methodology and data set (EFB) are a rigorous and longstanding method for measuring sustainability through trade and consumption worldwide. It goes through regular methodological advancements and is used by countries and researchers worldwide. However, the uptake of the approach is lacking across Canadian cities and sustainability groups. This study assessed the understanding, and perceptions of EFB among sustainability stakeholders in Canada to identify barriers and opportunities for increased uptake. We conducted 23 interviews with stakeholders from non-governmental and governmental organizations across western, central, and eastern Canada. The data was analyzed through an affinity sort and revealed themes which resulted in a broader research agenda focusing on social science questions centered around EFB. The identified areas for future research include source data, complexity and scale, behaviour, and policy. The resulting research agenda informed by stakeholders aims to enhance and broaden the use of EFB. The research agenda brings EFB into new areas of inquiry relevant to diverse sectors while also fostering multidisciplinary approaches. Advancing EFB methodologies and applications will enable researchers to contribute more significantly to global sustainability efforts.

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.

Digital formation processes: A high-frequency, large-scale investigation

Large sources of digital trace data (i.e. “Big Data”) have become increasingly important in the study of material culture. However, akin to the offline material culture traditionally studied by archaeologists, digital trace data is rarely a passive reflection of human behavior – it is a complex palimpsest produced through a variety of erasure and accretion formation processes. To better understand how digital trace palimpsests are formed and how digital formation processes influence and inform our ability to interpret the offline material processes they index, we introduce a computational method – high-frequency archaeological survey – which allows us to observe digital formation processes at a high temporal resolution, as well as a large spatial scale. Using this method every hour for one month, we surveyed posts from across the United States in Craigslist's “Free Stuff” category (popularly called “Curb Alert”), a user-generated source of big digital trace data, indexing material things that have been placed on users' curbs for removal by scavengers or trash collectors. For each post, we observed its time-to-erasure and any edits that were made during the study period – finding that the posts that survive represent a biased sample of those that were posted over the course of the month, conditioned by how recently and on what day the post is posted, the material characteristics of things that are posted about, as well as regional variation. Far from only being evidence of biased end-of-month data, however, we show that further analysis of identified digital formation processes can be an important object of study in its own right – in this case, shedding new light on social scientific questions linking the exchange of “free stuff” with the process of social stratification and urban inequality in the United States. Overall, our findings suggest the importance of accounting for and explicitly analyzing digital formation processes in studies that utilize digital trace data.

Analyzing Geography Questions in Social Studies, Science and Primary School Teaching Field Knowledge Tests According to Subject Distribution

Analyzing Geography Questions in Social Studies, Science and Primary School Teaching Field Knowledge Tests According to Subject Distribution

Social science – STEM collaborations in agriculture, food and beyond: an STSFAN manifesto

Interdisciplinary research needs innovation. As an action-oriented intervention, this Manifesto begins from the authors’ experiences as social scientists working within interdisciplinary science and technology collaborations in agriculture and food. We draw from these experiences to: 1) explain what social scientists contribute to interdisciplinary agri-food tech collaborations; (2) describe barriers to substantive and meaningful collaboration; and (3) propose ways to overcome these barriers. We encourage funding bodies to develop mechanisms that ensure funded projects respect the integrity of social science expertise and incorporate its insights. We also call for the integration of social scientific questions and methods in interdisciplinary projects from the outset, and for a genuine curiosity on the part of STEM and social science researchers alike about the knowledge and skills each of us has to offer. We contend that cultivating such integration and curiosity within interdisciplinary collaborations will make them more enriching for all researchers involved, and more likely to generate socially beneficial outcomes.

A Method for Estimating Individual Socioeconomic Status of Twitter Users

The rise of social media has opened countless opportunities to explore social science questions with new data and methods. However, research on socioeconomic inequality remains constrained by limited individual-level socioeconomic status (SES) measures in digital trace data. Following Bourdieu, we argue that the commercial and entertainment accounts Twitter users follow reflect their economic and cultural capital. Adapting a political science method for inferring political ideology, we use correspondence analysis to estimate the SES of 3,482,652 Twitter users who follow the accounts of 339 brands in the United States. We validate our estimates with data from the Facebook Marketing application programming interface, self-reported job titles on users’ Twitter profiles, and a small survey sample. The results show reasonable correlations with the standard proxies for SES, alongside much weaker or nonsignificant correlations with other demographic variables. The proposed method opens new opportunities for innovative social research on inequality on Twitter and similar online platforms.

The Genesis of Theory and Practice

One of the questions in social science is about the relationship between theory and practice. It goes back to the ancient Greek philosophers whose world was strictly separated into polis and oikos. The actors of polis were engaged in the formation of a democratic society requiring active action in the sense of vita activa. According to Arendt, with the decline of the polis and the emergence of the new forms of the society, vita activa was initially set in opposition to vita contemplativa and then later devalued in favour of vita contemplativa. However, with Galilei and Kant, there has been a counter-movement, which no longer understood theory as isolating oneself from the world but as shaping social realities. Theory and practice are joined today by the concept of research. The relationship between theory and practice will be examined initially within a historical perspective offering the genesis. Then the features of some institutions are discussed in terms of their communications with theory and practice and redefined accordingly.

Pelatihan Pengembangan Kompetensi dan Competitiveness Siswa Di Bidang Ilmu Sosial

Competence and skills of students must continue to be honed in order to further develop and be competitive. In addition, their competitive spirit must also be grown so that their spirit of achievement will automatically emerge and be able to compete at the national level. Through this training, it is hoped that students will be able to develop their competence and grow their competitive spirit. This training is carried out by enriching social science questions and motivating students by informing them of the benefits that will be obtained in achieving. This training activity was attended by Grade 9 Social Sciences students with great enthusiasm. This can be seen from the results of their learning evaluation showing that most of the scores obtained were very satisfying. In addition, it can be seen from the way students pay attention and their activeness in class.

Cooperation without punishment

A fundamental question in social and biological sciences is whether self-governance is possible when individual and collective interests are in conflict. Free riding poses a major challenge to self-governance, and a prominent solution to this challenge has been altruistic punishment. However, this solution is ineffective when counter-punishments are possible and when social interactions are noisy. We set out to address these shortcomings, motivated by the fact that most people behave like conditional cooperators—individuals willing to cooperate if a critical number of others do so. In our evolutionary model, the population contains heterogeneous conditional cooperators whose decisions depend on past cooperation levels. The population plays a repeated public goods game in a moderately noisy environment where individuals can occasionally commit mistakes in their cooperative decisions and in their imitation of the role models’ strategies. We show that, under moderate levels of noise, injecting a few altruists into the population triggers positive reciprocity among conditional cooperators, thereby providing a novel mechanism to establish stable cooperation. More broadly, our findings indicate that self-governance is possible while avoiding the detrimental effects of punishment, and suggest that society should focus on creating a critical amount of trust to harness the conditional nature of its members.

Is Mentalizing Essential to Predict Human Network Size? Reexamining the Social Brain Hypothesis From a Social Network Perspective

One central question in social science and evolutionary anthropology is how humans can form and maintain large social networks. The social brain hypothesis argues that humans use their mentalizing ability to read others’ minds for the development of dyadic relationships in layered social networks. However, previous empirical studies have not directly examined the association between mentalizing and the size of the active network located at the outermost layer. By introducing a social network perspective, we predicted that individuals use their mentalizing ability not only to form and maintain dyadic relationships but also to belong to multiple communities, which indirectly expands the active network size. We collected data from undergraduates in Japan (N = 175) to examine how mentalizing is linked to the size of online social networks. Mentalizing was positively associated with the number of dyads but not with the number of communities and the active network size. These findings suggest that the social brain hypothesis has limited validity, and there is a need for more careful explanations surrounding the psychological and structural underpinnings of large human social networks.

A framework for privacy preserving digital trace data collection through data donation

A potentially powerful method of social-scientific data collection and investigation has been created by an unexpected institution: the law. Article 15 of the EU’s 2018 General Data Protection Regulation (GDPR) mandates that individuals have electronic access to a copy of their personal data, and all major digital platforms now comply with this law by providing users with “data download packages” (DDPs). Through voluntary donation of DDPs, all data collected by public and private entities during the course of citizens’ digital life can be obtained and analyzed to answer social-scientific questions – with consent. Thus, consented DDPs open the way for vast new research opportunities. However, while this entirely new method of data collection will undoubtedly gain popularity in the coming years, it also comes with its own questions of representativeness and measurement quality, which are often evaluated systematically by means of an error framework. Therefore, in this paper we provide a blueprint for digital trace data collection using DDPs, and devise a “total error framework” for such projects. Our error framework for digital trace data collection through data donation is intended to facilitate high quality social-scientific investigations using DDPs while critically reflecting its unique methodological challenges and sources of error. In addition, we provide a quality control checklist to guide researchers in leveraging the vast opportunities afforded by this new mode of investigation.

The landscape of aging.

Aging is characterized by a progressive deterioration of physiological integrity, leading to impaired functional ability and ultimately increased susceptibility to death. It is a major risk factor for chronic human diseases, including cardiovascular disease, diabetes, neurological degeneration, and cancer. Therefore, the growing emphasis on “healthy aging” raises a series of important questions in life and social sciences. In recent years, there has been unprecedented progress in aging research, particularly the discovery that the rate of aging is at least partly controlled by evolutionarily conserved genetic pathways and biological processes. In an attempt to bring full-fledged understanding to both the aging process and age-associated diseases, we review the descriptive, conceptual, and interventive aspects of the landscape of aging composed of a number of layers at the cellular, tissue, organ, organ system, and organismal levels.

HATE SPEECH ON SOCIAL MEDIA: WITTGENSTEIN’S LANGUAGE GAMES THEORY

One of the most prevalent concerns on social media is hate speech. Because hate speech is mainly transmitted in text form on social media, linguistic analysis is required to determine the meaning of the hate speech. This study aims to look at the view of hate speech on social media using a literature study technique based on the Wittgenstein language game theory approach. According to Wittgenstein, language does not have a single logical structure but is complicated in its use in human life, which spans a wide range of activities. Previous research has looked at the meaning linked with language use in social media. As Wittgenstein proposes, the finding of the research is That ordinary language collected through social media data may be utilized to offer direct answers to social scientific questions. Online media that allows people to represent themselves and cooperate to share, connect with other users, and form virtual social relationships are referred to as social media. Starting with the presentation of quotes, there will be a "language game" with the concept of "from, by, and for." Finally, the author proposes using two markers to analyze hate speech on social media: typology and message content

A cross-verified database of notable people, 3500BC-2018AD

A new strand of literature aims at building the most comprehensive and accurate database of notable individuals. We collect a massive amount of data from various editions of Wikipedia and Wikidata. Using deduplication techniques over these partially overlapping sources, we cross-verify each retrieved information. For some variables, Wikipedia adds 15% more information when missing in Wikidata. We find very few errors in the part of the database that contains the most documented individuals but nontrivial error rates in the bottom of the notability distribution, due to sparse information and classification errors or ambiguity. Our strategy results in a cross-verified database of 2.29 million individuals (an elite of 1/43,000 of human being having ever lived), including a third who are not present in the English edition of Wikipedia. Data collection is driven by specific social science questions on gender, economic growth, urban and cultural development. We document an Anglo-Saxon bias present in the English edition of Wikipedia, and document when it matters and when not.

Evoked and transmitted culture models: Using bayesian methods to infer the evolution of cultural traits in history.

A central question in behavioral and social sciences is understanding to what extent cultural traits are inherited from previous generations, transmitted from adjacent populations or produced in response to changes in socioeconomic and ecological conditions. As quantitative diachronic databases recording the evolution of cultural artifacts over many generations are becoming more common, there is a need for appropriate data-driven methods to approach this question. Here we present a new Bayesian method to infer the dynamics of cultural traits in a diachronic dataset. Our method called Evoked-Transmitted Cultural model (ETC) relies on fitting a latent-state model where a cultural trait is a latent variable which guides the production of the cultural artifacts observed in the database. The dynamics of this cultural trait may depend on the value of the cultural traits present in previous generations and in adjacent populations (transmitted culture) and/or on ecological factors (evoked culture). We show how ETC models can be fitted to quantitative diachronic or synchronic datasets, using the Expectation-Maximization algorithm, enabling estimating the relative contribution of vertical transmission, horizontal transmission and evoked component in shaping cultural traits. The method also allows to reconstruct the dynamics of cultural traits in different regions. We tested the performance of the method on synthetic data for two variants of the method (for binary or continuous traits). We found that both variants allow reliable estimates of parameters guiding cultural evolution, and that they outperform purely phylogenetic tools that ignore horizontal transmission and ecological factors. Overall, our method opens new possibilities to reconstruct how culture is shaped from quantitative data, with possible application in cultural history, cultural anthropology, archaeology, historical linguistics and behavioral ecology.

Knowledge Priorities on Climate Change and Water in the Upper Indus Basin: A Horizon Scanning Exercise to Identify the Top 100 Research Questions in Social and Natural Sciences

AbstractRiver systems originating from the Upper Indus Basin (UIB) are dominated by runoff from snow and glacier melt and summer monsoonal rainfall. These water resources are highly stressed as huge populations of people living in this region depend on them, including for agriculture, domestic use, and energy production. Projections suggest that the UIB region will be affected by considerable (yet poorly quantified) changes to the seasonality and composition of runoff in the future, which are likely to have considerable impacts on these supplies. Given how directly and indirectly communities and ecosystems are dependent on these resources and the growing pressure on them due to ever‐increasing demands, the impacts of climate change pose considerable adaptation challenges. The strong linkages between hydroclimate, cryosphere, water resources, and human activities within the UIB suggest that a multi‐ and inter‐disciplinary research approach integrating the social and natural/environmental sciences is critical for successful adaptation to ongoing and future hydrological and climate change. Here we use a horizon scanning technique to identify the Top 100 questions related to the most pressing knowledge gaps and research priorities in social and natural sciences on climate change and water in the UIB. These questions are on the margins of current thinking and investigation and are clustered into 14 themes, covering three overarching topics of “governance, policy, and sustainable solutions”, “socioeconomic processes and livelihoods”, and “integrated Earth System processes”. Raising awareness of these cutting‐edge knowledge gaps and opportunities will hopefully encourage researchers, funding bodies, practitioners, and policy makers to address them.

The Essential Role of Statistical Inference in Evaluating Electoral Systems: A Response to DeFord et al.

AbstractKatz, King, and Rosenblatt (2020, American Political Science Review 114, 164–178) introduces a theoretical framework for understanding redistricting and electoral systems, built on basic statistical and social science principles of inference. DeFord et al. (2021, Political Analysis, this issue) instead focuses solely on descriptive measures, which lead to the problems identified in our article. In this article, we illustrate the essential role of these basic principles and then offer statistical, mathematical, and substantive corrections required to apply DeFord et al.’s calculations to social science questions of interest, while also showing how to easily resolve all claimed paradoxes and problems. We are grateful to the authors for their interest in our work and for this opportunity to clarify these principles and our theoretical framework.

Analisis soal higher order thinking skill (HOTS) pembelajaran IPS kelas IV di sekolah dasar

<em>The purpose of this research is to explain the suitability between problem and concept of HOTS in question of social sciences semester 1 of grade fourth Elementary School Kerten 2 Surakarta for the 2020/2021 academic year. This research uses thinking level and stimulus indicators. The results of this research shows that there is no conformity between hots concept and problem because the percentage of HOTS on social science questions only 9%. The primary data in this research is a document evaluate of the learning results of theme 1 to theme 5 social sciences grade fourth Elementary School Kerten 2 Surakarta. The results of this research is useful to improve teachers quality when make a question with cognitive levels to learners so they can make some levels on their assessements. In addition, this research is intend as an option to determine the criteria of the questions to improve the critical thinking of learners.</em>

Quantity-quality trade-off in the acquisition of token preference by capuchin monkeys (Sapajus spp.).

Money represents a cornerstone of human modern economies and how money emerged as a medium of exchange is a crucial question for social sciences. Although non-human primates have not developed monetary systems, they can estimate, combine and exchange tokens. Here, we evaluated quantity-quality trade-offs in token choices in tufted capuchin monkeys as a first step in the investigation of the generalizability of tokens as reinforcers, which is a potentially relevant factor underlying the emergence of money in humans. We measured capuchins' exchange preferences when they were repeatedly provided with 10 units of three token types yielding food combinations varying in quantity and quality. Overall, capuchins maximized their quantitative payoff, preferring tokens associated with a higher food amount, rather than showing violations of rationality. However, some individuals did not maximize their qualitative payoff, possibly because of conditional valuation effects or owing to the choice overload phenomenon, according to which too many options reduce the accuracy of choice. Our study supports the importance of comparative research to finely analyse the multiple components shaping the economic behaviours of other species, possibly to achieve a more comprehensive, evolutionary- and ecologically based understanding of human economic behaviour. This article is part of the theme issue 'Existence and prevalence of economic behaviours among non-human primates'.

Another silver lining?: Anthropological perspectives on the promise and practice of relaxed restrictions for telemedicine and medication-assisted treatment in the context of COVID-19.

As a response to the COVID-19 pandemic, the United States Drug Enforcement Administration (DEA) has temporarily relaxed restrictions to serve people who are opioid dependent during social distancing mandates. Changes include allowing patients to take home more doses of methadone and buprenorphine rather than coming to the clinic every day (for methadone) or weekly (for buprenorphine) and relaxed restrictions on telehealth delivery. Telemedicine Program representatives have described the relaxing of federal regulations as a "silver lining" to the COVID-19 pandemic. Drawing from medical anthropology approaches to epidemic surveillance and understandings of risk, we critically evaluate media representations of recent changes to telemedicine, prescribing, and opioid treatment delivery. Ethnographic research with providers and stakeholders in Arizona from 2017 to the present add insight to our analysis of media reports on these topics. Our findings demonstrate that media portrayal of access to medication-assisted treatment (MAT) as the key to preventing both COVID-19 and overdose among people who are opioid dependent misses important risks and potential inequities. Applied social science questions raised by the new guidelines include: who receives take-home doses of methadone and buprenorphine and why; and how media representations of risk and benefit rationales shape real-world policy and practice.