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"Scaling (Social sciences)"
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Scale : discourse and dimensions of social life
\"Wherever we turn, we see diverse things scaled for us, from cities to economies to history to love. We know scale by many names, and through many familiar antinomies: 'local' and 'global,' 'micro' and 'macro,' 'events' and the 'longue durâee.' Even the most critical amongst us often proceed with our analysis as if such scales are the readymade platforms of social life, rather than asking how, why, and to what effect scalar distinctions are forged in the first place? How do scalar distinctions help actors and analysts alike make sense of and navigate their social worlds? What do they reveal and what do they conceal? How are scales construed and what effects do they have on the way the people who abide by them think and act? This path-breaking volume attends to the practical labor of scale making and the communicative practices this labor requires. Ethnographically, the chapters demonstrate that scale is practice and process before it is product, whether in the work of projecting 'the commons,' claiming access to 'the big picture,' or scaling the seriousness of a crime\"--Provided by publisher.
Book
Optimally generate policy-based evidence before scaling
Social scientists have increasingly turned to the experimental method to understand human behaviour. One critical issue that makes solving social problems difficult is scaling up the idea from a small group to a larger group in more diverse situations. The urgency of scaling policies impacts us every day, whether it is protecting the health and safety of a community or enhancing the opportunities of future generations. Yet, a common result is that, when we scale up ideas, most experience a ‘voltage drop’—that is, on scaling, the cost–benefit profile depreciates considerably. Here I argue that, to reduce voltage drops, we must optimally generate policy-based evidence. Optimality requires answering two crucial questions: what information should be generated and in what sequence. The economics underlying the science of scaling provides insights into these questions, which are in some cases at odds with conventional approaches. For example, there are important situations in which I advocate flipping the traditional social science research model to an approach that, from the beginning, produces the type of policy-based evidence that the science of scaling demands. To do so, I propose augmenting efficacy trials by including relevant tests of scale in the original discovery process, which forces the scientist to naturally start with a recognition of the big picture: what information do I need to have scaling confidence?
To reduce voltage drops—the depreciation of the cost–benefit profile when scaling up solutions to social problems—sufficient policy-based evidence must be generated before policymakers scale up the project.
Journal Article
Latent Feature Extraction for Process Data via Multidimensional Scaling
Computer-based interactive items have become prevalent in recent educational assessments. In such items, detailed human–computer interactive process, known as response process, is recorded in a log file. The recorded response processes provide great opportunities to understand individuals’ problem solving processes. However, difficulties exist in analyzing these data as they are high-dimensional sequences in a nonstandard format. This paper aims at extracting useful information from response processes. In particular, we consider an exploratory analysis that extracts latent variables from process data through a multidimensional scaling framework. A dissimilarity measure is described to quantify the discrepancy between two response processes. The proposed method is applied to both simulated data and real process data from 14 PSTRE items in PIAAC 2012. A prediction procedure is used to examine the information contained in the extracted latent variables. We find that the extracted latent variables preserve a substantial amount of information in the process and have reasonable interpretability. We also empirically prove that process data contains more information than classic binary item responses in terms of out-of-sample prediction of many variables.
Journal Article
Differential Item Functioning via Robust Scaling
This paper proposes a method for assessing differential item functioning (DIF) in item response theory (IRT) models. The method does not require pre-specification of anchor items, which is its main virtue. It is developed in two main steps: first by showing how DIF can be re-formulated as a problem of outlier detection in IRT-based scaling and then tackling the latter using methods from robust statistics. The proposal is a redescending M-estimator of IRT scaling parameters that is tuned to flag items with DIF at the desired asymptotic type I error rate. Theoretical results describe the efficiency of the estimator in the absence of DIF and its robustness in the presence of DIF. Simulation studies show that the proposed method compares favorably to currently available approaches for DIF detection, and a real data example illustrates its application in a research context where pre-specification of anchor items is infeasible. The focus of the paper is the two-parameter logistic model in two independent groups, with extensions to other settings considered in the conclusion.
Journal Article
The spatiotemporal scaling laws of urban population dynamics
Human mobility is becoming increasingly complex in urban environments. However, our fundamental understanding of urban population dynamics, particularly the pulsating fluctuations occurring across different locations and timescales, remains limited. Here, we use mobile device data from large cities and regions worldwide combined with a detrended fractal analysis to uncover a universal spatiotemporal scaling law that governs urban population fluctuations. This law reveals the scale invariance of these fluctuations, spanning from city centers to peripheries over both time and space. Moreover, we show that at any given location, fluctuations obey a time-based scaling law characterized by a spatially decaying exponent, which quantifies their relationship with urban structure. These interconnected discoveries culminate in a robust allometric equation that links population dynamics with urban densities, providing a powerful framework for predicting and managing the complexities of urban human activities. Collectively, this study paves the way for more effective urban planning, transportation strategies, and policies grounded in population dynamics, thereby fostering the development of resilient and sustainable cities.
Urban populations ebb and flow as the pulse of human mobility reshapes the cityscape. This paper shows a spatiotemporal scaling laws revealing hidden patterns in these dynamic shifts, linking them to the urban fabric’s structure, density, and functionality.
Journal Article
Structure and evolution of innovation research in the last 60 years: review and future trends in the field of business through the citations and co-citations analysis
The field of innovation studies has grown considerably in the last four decades, which has led to the emergence of new approaches and theoretical aspects that need to be examined and considered. Therefore, this paper aims to understand what are the main theoretical pillars that support the structure of innovation theories and fields, how it evolved over the years and what are the directions that lead to future trends in innovation research. The procedure consists in a mix-methods using the citation and co-citation analysis associated with bibliometric methods, Social Network Analysis, and a systematic review of the literature. The results were validated by Delphi with academic specialists in innovation. Considering publications between 1956 and 2016 divided into four 15-years timespan, the longitudinal analysis results indicate the evolution of the main streams of thoughts that support the current innovation research fields and depict a research orientation for future works that can be developed to generate relevant contributions for the theoretical development of the area. This paper differentiates itself bringing results based on a large database, by the research methods employed, and by the perspective adopted provides solid contributions to the understanding of the past, present, and future of the scientific research in innovation to business administration field.
Journal Article
Soil carbon sequestration as a climate strategy
Countries and companies with net-zero emissions targets are considering carbon removal strategies to compensate for remaining greenhouse gas emissions. Soil carbon sequestration is one such carbon removal strategy, and policy and corporate interest is growing in figuring out how to motivate farmers to sequester more carbon. But how do farmers in various cultural and geographic contexts view soil carbon sequestration as a climate mitigation or carbon removal strategy? This article systematically reviews the empirical social science literature on farmer adoption of soil carbon sequestration practices and participation in carbon markets or programs. The article finds thirty-seven studies over the past decade that involve empirical research with soil carbon sequestering practices in a climate context, with just over a quarter of those focusing on the Global South. A central finding is co-benefits are a strong motivator for adoption, especially given minimal carbon policies and low carbon prices. Other themes in the literature include educational and cultural barriers to adoption, the difference between developing and developed world contexts, and policy preferences among farmers for soil carbon sequestration incentives. However, we argue that given the rising profile of technical potentials and carbon credits, this peer-reviewed literature on the social aspects of scaling soil carbon sequestration is quite limited. We discuss why the social science literature is so small, and what this research gap means for efforts to achieve higher levels of soil carbon sequestration. We conclude with a ten-point social science research agenda for social science on soil carbon—and some cautions about centering carbon too strongly in research and policy.
Journal Article
Ensuring Positiveness of the Scaled Difference Chi-square Test Statistic
A scaled difference test statistic
that can be computed from standard software of structural equation models (SEM) by hand calculations was proposed in Satorra and Bentler (Psychometrika 66:507–514,
2001
). The statistic
is asymptotically equivalent to the scaled difference test statistic
introduced in Satorra (Innovations in Multivariate Statistical Analysis: A Festschrift for Heinz Neudecker, pp. 233–247,
2000
), which requires more involved computations beyond standard output of SEM software. The test statistic
has been widely used in practice, but in some applications it is negative due to negativity of its associated scaling correction. Using the implicit function theorem, this note develops an improved scaling correction leading to a new scaled difference statistic
that avoids negative chi-square values.
Journal Article
Understanding the Diverse Scaling Strategies of Social Enterprises as Hybrid Organizations: The Case of Renewable Energy Cooperatives
This article seeks to shed light on the diversity of scaling strategies of social enterprises, which can be considered as emblematic hybrid organizations. By comparing three Flemish renewable energy cooperatives with contrasted scaling strategies, the article shows how these strategies can be understood in relation to the organizational mission as imprinted at the founding. We extend the notion of hybridity beyond the combination of institutional logics to highlight the interest orientation (mutual vs. general interest). Unlike what is suggested in extant literature, we find that mutual interest orientation may be associated with “scale-up,” business growth strategies, while general interest orientation may lead to less growth-focused “scale-out” and “scale-deep” strategies. The findings illuminate aspects of the hybrid nature of social enterprises by explaining their diverse scaling strategies and extend the notion of imprinting to the interorganizational level by highlighting how social enterprises may collaborate to collectively achieve the pursuit of their multiple missions.
Journal Article