Context Of Social Sciences Research Articles

The reporting completeness of observational systematic reviews and meta-analysis in social science could be improved: a cross-sectional survey

ObjectiveTo evaluate and compare the reporting quality of observational systematic reviews and meta-analyses (OSRMA) published in Chinese and English-language social science journals using the Meta-analyses Of Observational Studies in Epidemiology (MOOSE) guideline. Study design and settingWe searched the Social Science Core Index (SSCI) via Web of Science and the Chinese Social Science Core Index (CSSCI) via China National Knowledge Infrastructure (CNKI) databases for OSRMAs published from 2012 to 2022 (before December 2022). The process of literature search, selection, and data extraction were performed double blind. ResultsWe identified 634 OSRMAs, of which 349 were in English-language journals and 285 in Chinese-language journals. The mean reporting completeness rate was 54.6%, and reviews in English had higher reporting completeness than those in Chinese (55.2% vs. 53.9%). All the reviews reported well on background, method, and conclusion, with average reporting rates of 68.1%, 65.2%, and 88.8%, respectively. However, the reporting of search strategy was ignored, with an average rate of 42.9% for reviews in English and 25.8% for reviews in Chinese, especially on the qualifications of searchers, effort to include all available studies, search-software used, handling unpublished studies, and contact with authors. The reporting transparency of these reviews was statistically significantly influenced by multiple review factors, including the language of journals, year of publication, the number of authors, the reporting guideline followed, and the declaration of funding source. ConclusionOSRMAs in social science demonstrate low reporting quality, especially in Chinese-language journals. We suggest adapting the MOOSE guideline to the social science context and promoting its use among researchers and reviewers in this field.

Finding the Historical Imagination: Teaching Modern British History in a Social Sciences Context.

Finding the Historical Imagination: Teaching Modern British History in a Social Sciences Context.

Technological Encounters in a Knowledge Economy: An Epistemic X-Ray.

Climate emergency is a planetary health and systems science challenge because human health, nonhuman animal health, and the health of the planetary ecosystems are coproduced and interdependent. Yet, we live in a time when climate emergency is tackled by platitudes and weak reforms instead of structural and systems changes, and with tools of the very same systems and metanarratives, for example, infinite growth at all costs, that are causing climate change in the first place. Seeking solutions to problems from within the knowledge frames and metanarratives that are causing the problems reproduces the same problems across time and geographies. This article examines and underlines the importance of an epistemological gaze on knowledge economy, an epistemological X-ray, as another solution in the toolbox of decolonial and other social justice struggles in an era of climate emergency. Epistemology questions and excavates the metanarratives embedded in knowledge forms that are popular, dominant, and hegemonic as well as knowledges that are silent, omitted, or erased. In this sense, epistemology does not take the "archives" of data and knowledge for granted but asks questions such as who, when, how, and with what and whose funding the archive was built, and what is included and left out? Epistemological choices made by innovators, funders, and knowledge actors often remain opaque in knowledge economies. Epistemology research is crucial for science and innovations to be responsive to planetary society and climate emergency and mindful of the social, political, neocolonial, and historical contexts of science and technology in the 21st century.

The concept of inclusive communication style on the way to inclusive stylistics

Abstract The contouring of inclusive stylistics as a new key concept of this discipline is inspired by panchronic continuity (especially) with rhetorical and stylistic considerations, as well as with considerations originating in the wider context of social sciences in the intersection of scientistic and antiscientist methodological frameworks. The inclusive style is a pillar of stylistics that aims to meet the communication needs of civil society of the 21st century. I integrate considerations on the way to inclusive stylistics (as a subset of interactional stylistics) in the spirit of the cognitive pluralism of the time (Gajda 2022, p. 8) as my contribution to the plurality of stylistic considerations in the name of unity in the diversity of the discipline. The attached text is an entry “shoot” to the team project of inclusive stylistics.

Feminism Is for Everyone: Scientists, Too.

Critically informed engagement in politics and the knowledge of social theory help democratize knowledge production, and redress power asymmetries in science and society. A feminist lens is one of the many ways in which power asymmetries in science can be critically unpacked and interrupted. There are many strands of feminism and feminist theory that differ in their approaches to resist patriarchy and injustices in science and society. As an example, I adopt here the definition of feminism of the late cultural critic bell hooks because her works underscore that feminism is an intersectional liberatory methodology for everyone to resist multiple forms of oppression simultaneously. Queer theory is a strand of social theory that came to prominence since the 1990s in particular. Queer feminism continues to shape feminist writing on science cultures and the knowledge-based innovations contemporary science strives to accomplish. Systems science brings about systems thinking, and that includes rethinking science as culture beyond a narrow realm of technology, and being cognizant of the broader social, feminist, queer, and political contexts of science around the world.

Group concept mapping – bridging the gap between conceptual papers and empirical research

AbstractWith growing internationalism, there is a shift in research patterns in developing countries, especially China and India, generating vital and contemporary research areas that are beginning to challenge the existing Western‐dominated research literature in social sciences. Yet, many of the new ideas within conceptual papers by the social sciences are not empirically validated, let alone operationalized. This is where the group concept mapping method can play a role in bridging the gap between phenomenal conceptualization and having an empirically valid model that can then be operationalized. The group concept mapping process involves five steps: create statements, sort statements, run multidimensional scaling (MDS) of sorted units, run cluster analysis, and label the clusters. This approach allows for the collective thoughts of a pre‐defined group to be collected and organized into a tangible output with academic rigor. This paper offers an overview of the group concept mapping methodology, discussing the processes of the method, how the method can be utilized fully within the business and broader social science context, and the strengths, weaknesses, and practical implications of group concept mapping.

Secondary Qualitative Research Methodology Using Online Data within the Context of Social Sciences

Qualitative research using interviews is a crucial and established inquiry method in social sciences to ensure that the study outputs represent the researched people and area rather than those who are researching. However, first hand primary data collection is not always possible, often due to external circumstances. Additionally, the use of secondary data, particularly open data, is progressively preferred to increase efficiency and gain geographical breadth. Therefore, this paper proposes a new step-by-step secondary qualitative inquiry methodology for online, publicly available interview data. Such procedural approach can help increase rigor, explicitly consider and mitigate potential pitfalls, and expand the research community’s datasets. The 7-step methodology is based on a hybrid approach with elements of pragmatic qualitative approach, discursive grounded theory, and narrative approach and refers to research ethical principles of autonomy, equity, and diversity. One of the proposed steps is data quality assessment, which consists of quality assessment of data context and data content with a total of 16 quality dimensions to filter the collected data. The data analysis method comprises of content analysis for dataset categorization and thematic discourse analysis to answer the pre-set research questions. Additionally, the methodology covers the ethical and legal considerations relating to secondary online data and reporting the research findings of such data. By providing an example in the field of forced migration, we demonstrate how the methodology provides structure when conducting secondary qualitative research.

Examining heterogeneity of education intervention effects using quantile mixed models: a re-analysis of a cluster-randomized controlled trial of a fluency-based mathematics intervention

ABSTRACT Traditionally, cluster randomized controlled trials are analyzed with the average intervention effect of interest. However, in populations that contain higher degrees of heterogeneity or variation may differ across different values of a covariate, which may not be optimal. Within education and social science contexts, exploring the variation in magnitude of treatment effect at different points in the population can indicate where the intervention is most effective rather than assuming an average effect. Data from [Owen, K.L., et al., 2021. Implementation support improves outcomes of a fluency-based mathematics strategy: A cluster-randomized controlled trial. Journal of research on educational effectiveness, 14 (3), 523–542.] were reanalyzed using three modeling approaches: conditional mean-modeling reporting the average treatment effect using linear mixed models, and two quantile regression-based methods. Quantile regressions report the quantile treatment effects at different percentiles: 10th, 25th, 50th, 75th and 90th. For the Quantile approaches, a significant intervention effect in the median to upper quantiles was found and linear quantile mixed model showed improved fit over the other approaches. An improved picture of intervention effects may be apparent using quantile regression methods when analyzing cluster randomized trials that have heterogeneous error variance. In particular, the linear quantile mixed model shows improved model fit allowing a multilevel framework to include random effects. There is considerable scope to extend this framework to incorporate more complex RCT designs.

Reflections on Preregistration: Core Criteria, Badges, Complementary Workflows

Clinical trials are routinely preregistered. In psychology and the social sciences, however, only a small percentage of studies are preregistered, and those preregistrations often contain ambiguities. As advocates strive for broader uptake and effective use of preregistration, they can benefit from drawing on the experience of preregistration in clinical trials and adapting some of those successes to the psychology and social sciences context. We recommend that individuals and organizations who promote preregistration: (1) Establish core preregistration criteria required to consider a preregistration complete; (2) Award preregistered badges only to articles that meet the badge criteria; and (3) Leverage complementary workflows that provide a similar function as preregistration.

SCIENCE, TECHNOLOGY AND SOCIETY THROUGH THE PRISM OF EDUCATION

The current article examines various concepts of technology, science, engineering, scientific knowledge, technical knowledge, technical knowledge, empirical knowledge and their respective implications in the social context. Both theoretical and practical knowledge are products of knowledge and are built step by step in the process of social interaction. This knowledge is a cultural heritage of societies and is under constant construction and reconstruction. Science and technology are historical products and social knowledge organized and systematized in continuous creativity. The concepts of science, technology, and society and education as a social institution are closely related, as they both recognize the interconnectedness of technology, society, and education. The STS framework is an interdisciplinary approach that emphasizes the interdependence of scientific knowledge, technological development, and societal values and norms. According to this framework, science and technology are not neutral or objective entities, but are shaped by and shape social, cultural, economic, and political factors. STS scholars argue that understanding the social context of science and technology is essential for developing ethical and effective policies and practices.

Addiction, Waste(d) Labor, and the Debate of the Carpenter's Tools

Addiction, Waste(d) Labor, and the <i>Debate of the Carpenter's Tools</i>

Qualitatively recognizing the dimensions of student environmental identity development within the classroom context

AbstractThis study qualitatively explored the process of student environmental identity development (sEID) within the highly social and structured context of elementary school science. Social practice theory was used as the lens to distinguish the dimensions of sEID that were visible during a curriculum‐based, in‐school program focused on the issue of pollution. Student narratives, collected from small group interviews and reflective journals, were prioritized to capture the process of students in context identifying as “being for the environment.” Data collected from 35 grade six students were qualitatively coded, a network diagram was used to visualize the relationships in the data, and a research vignette was constructed. Eight dimensions were recognized as contributing to sEID; the opportunity to be an environmental actor with peers, increased awareness of environmental threat, emotional responses, self‐recognition for environmental action, perceived agency, changed behavior across social contexts, social recognition for identity actions, and personal meaning. While many of these dimensions have been directly or indirectly discussed in the research on adult environmentalists, shifting the emphasis from group membership to the individual student in context led to the addition of two dimensions—personal meaning and emotional responses. Recognizing the eight dimensions of sEID is an important contribution to the literature as students engaging in environmental action as a requirement of school is distinct from the existing research. Identifying the dimensions of sEID can support the intentional design of learning sequences that foster environmental identities in school and beyond.

Virtual communities decision model (VCDM): An empirical validation in online social networks (OSNs) adoption among capital market investors

The COVID-19 epidemic has hastened the growth of Virtual Communities and is affecting virtually every part of work in the public and business sectors. Virtual communities, popular forums for communication and entertainment, increasingly affected the users’ decisions. Though many technology adoption models/theories are available, a distinctive model for decision-making in a virtual environment is scarce. This research developed the virtual communities’ decision model and empirically tested its performance. This study examined 16 well-established theories/models of information technology, social science, marketing, and behavioral finance and extracted nine constructs from 58 identified constructs considering theoretical cohesiveness along with the three-stage method proposed by Moore and Benbasat. A unified model for virtual communities’ decisions (VCDM) is developed and validated using the data collected from individual capital market investors in Bangladesh. The structural equation modeling technique is used to analyze the data. The upshot implies that VCDM performs adequately and explains the maximum variances in intention to decision and investment. VCDM also outperforms the majority of the related theoretical models. The acceptance levels of fit indices and all significant relationships among different constructs are also empirically validated. The moderating effect of the virtual group use experience is also confirmed. Future research can use VCDM in marketing, behavioral finance, ecommerce, information systems and social science context. VCDM thus facilitates a beneficial tool for managers, service providers, and other users to assess the likelihood of effectiveness for decisions in a virtual environment.

Exploring Women's Retirement Literature through Bibliometric Analysis Using VOSviewer

This paper aims to analyse the issue of women’s retirement (WR) literature through bibliometric analysis using VOSviewer, a programme for the visualisation of similarities (VOS). Publications focusing on women’s retirement were compiled from the Scopus database, with a total of 393 items spanning the years 1965 to 2021. The most prolific nations for retirement literature are the United States, United Kingdom, and Sweden, which reflects the affiliation analysis that correlates highly with published papers within specific institutions in those three countries. The issues were discussed within the context of social sciences, economics, econometrics, and finance, as well as psychology. This suggests an interlinking of women’s retirement with social and financial issues that might contribute towards psychological challenges for women. The most cited keywords, among others, are ‘retirement’, ‘women’ and ‘pension’, with thematic clusters being linked to ‘ageing’ and ‘health’. These could be linked to health problems that emerge because of ageing, and thus might be linked to the retirement wellbeing of women. The findings of this paper shed light on several implications that can be used as a guideline for researchers and act as a foundation before embarking on the emerging knowledge areas of women’s retirement.

Power swgee: GEE-based power calculations in stepped wedge cluster randomized trials.

Stepped wedge cluster randomized trials are increasingly being used to evaluate interventions in medical, public health, educational, and social science contexts. With the longitudinal and crossover nature of a SW-CRT, complex analysis techniques are often needed which makes appropriately powering SW-CRTs challenging. In this paper, we introduce a newly-developed SW-CRT power calculator, embedded within the power command in Stata. The power calculator assumes a marginal model (i.e., generalized estimating equations [GEE]) for the primary analysis of SW-CRTs, for which other currently available SW-CRT power calculators may not be suitable. The program accommodates complete cross-sectional and closed-cohort designs, and includes multilevel correlation structures appropriate for such designs. We discuss the methods and formulae underlying our SW-CRT calculator, and provide illustrative examples of the use of power swgee. We provide suggestions about the choice of parameters in power swgee, and conclude by discussing areas of future research which may improve the program.

Interdisciplinary research by accounting scholars: An exploratory study

There is a growing consensus around the pivotal role of interdisciplinary research (hereafter IDR) in achieving innovative results and addressing the challenges of modern societies, whose solutions are often beyond the scope of a single discipline. This paper builds on this literature to explore the trends in IDR and its evaluation in research quality assessments in the context of accounting studies by Italian scholars, even in comparison with disciplinary research. This exploratory study covers a da- taset of all articles published by Italian accounting scholars in international journals indexed in Scopus from 1985 to 2015 (1,233 articles). We operationalise IDR as diversity in the subject area of journals where the articles are published and diversity in the disciplinary sector of coauthors. Thus, the novelty of this article is that instead of using a single indicator of IDR, we consider the interaction of two alternative perspectives of analysis. The main findings reveal a relevant increase in disciplinary and interdisciplinary articles, with a comparatively smaller increase for IDR. Additionally, we observe that IDR by Italian accounting scholars is strongly oriented towards medical publi- cations. Regarding quality evaluation, the findings show a significantly higher eval- uation of disciplinary studies compared to IDR according to the criteria followed by the national assessment exercise (VQR). This explorative study contributes to the debate on IDR in two different ways. On the one hand, our study shows a relatively low growth of IDR in the under-re- searched context of social sciences in a non-Anglo-Saxon setting, where national research evaluations have stimulated radical changes in the features and outlets of scientific production. On the other hand, our results are consistent with the view that papers with a clear disciplinary focus receive comparatively higher evaluations be- cause the standards established for assessment are usually defined within the disci- pline.

Comparative Study of Teachers and Students Perceptions towards Science Technology Society and Environment (STSE) Approach

The main aim of this study was to compare the perceptions of secondary school science teachers and students towards Science, Technology, Society and Environment (STSE) approach. Quantitative survey design was used to investigate the problem. The population of the study consisted of all Government secondary school science teachers and students in the tehsil Adenzai. By using stratified sampling technique 90 science teachers and 737 science students were randomly selected for this study. A self-developed questionnaire consisted of multiple scales were used to collect data from the respondents. The study results show significant differences between the perceptions of science teachers and students regarding the concept of STSE approach, required training skills, social context of science, and usefulness of STSE approach for teaching of science. Rank order, frequency and percentage scores showed no difference between the perceptions of science teachers and students regarding aim of science education, hindering challenges in STSE approach and suggestions and recommendations for the implementation of STSE approach. It was recommended that science curriculum may be developed on the basis of STSE approach and science teachers may properly be trained to implement this approach in classroom for teaching science subjects

Emancipatory practice development in social welfare service evaluation – a worked example

Background: People accessing social welfare services are connected by service provision across health and social care, so there is a crossover in the work of practitioners in those fields. It would be beneficial for these professionals to share a language when it comes to evaluating the services they provide. Aim: This article sought to address the need to improve service evaluation across all health and social science disciplines, which are interconnected through provision of welfare-related services for individuals living in the UK. It aimed to highlight the value of a shared language across organisations that provide these services. Methods: A worked example is presented, applying emancipatory practice development as a cross-disciplinary framework with community practitioners, who shared views through a non-moderated focus group. Conclusion: Before any stakeholder views are sought, the first step in sustained transformation is practitioner reflections using reflexivity within a safe physical and emotional space. This enables practitioners first to reflect on whether their practice is authentically person-centred and second to consider how to devise creative methodologies for service evaluation. Implications for practice: Emancipatory practice development could be beneficial as a cross-disciplinary framework in applied social science contexts to develop a shared approach to service evaluation with healthcare colleagues Before engaging with any stakeholders, practitioners could benefit from engaging in reflexivity to encourage authentic reflection and creative person-centred methodologies Safe emotional and physical spaces are needed for authentic practitioner reflection

Social Futuring, Modern and Ancient

This article reviews and compares two approaches to the new, holistic, and multidisciplinary concept “Social Futuring,” which are expressed in two indices based on this concept, entitled the “Social Futuring Index” and the “Human Flourishing Index” (HFI). Broadly speaking, the Social Futuring Index is indebted to the broader context of modern social sciences, while the Human Flourishing Index attempts to update the scholastic moral philosophy, which was based primarily on the insights of Aristotle and Augustine, as combined by Thomas Aquinas (hence the HFI was previously called the “AAA Index”). Finally, we present the key elements of both indices and their measurement for individual countries from a comparative perspective.

A Topic Modeling Comparison Between LDA, NMF, Top2Vec, and BERTopic to Demystify Twitter Posts.

The richness of social media data has opened a new avenue for social science research to gain insights into human behaviors and experiences. In particular, emerging data-driven approaches relying on topic models provide entirely new perspectives on interpreting social phenomena. However, the short, text-heavy, and unstructured nature of social media content often leads to methodological challenges in both data collection and analysis. In order to bridge the developing field of computational science and empirical social research, this study aims to evaluate the performance of four topic modeling techniques; namely latent Dirichlet allocation (LDA), non-negative matrix factorization (NMF), Top2Vec, and BERTopic. In view of the interplay between human relations and digital media, this research takes Twitter posts as the reference point and assesses the performance of different algorithms concerning their strengths and weaknesses in a social science context. Based on certain details during the analytical procedures and on quality issues, this research sheds light on the efficacy of using BERTopic and NMF to analyze Twitter data.