scholarly journals Rethinking the elusive construct of global self-concept: A latent composite score as the apex of the Shavelson model

2020 ◽  
Author(s):  
Laura Braun ◽  
Sven Rieger ◽  
Marion Spengler ◽  
Richard Göllner ◽  
Norman Rose ◽  
...  

The multidimensional, hierarchical model of self-concept by Shavelson, Hubner, and Stanton (1976) is a cornerstone of modern self-concept research. Given the comprehensive research interest in it, it is surprising that one core aspect of this model has yet to be clarified: What is the best way to operationalize the elusive construct of global self-concept as the apex of the hierarchy? Previous research implemented global self-concept by applying reflective modeling procedures (e.g., second-order factor models) that followed a top-down logic, which assumes that global self-concept affects lower order self-concepts. However, theoretical considerations have often equally emphasized bottom-up processes, in which lower order self-concepts form a global self-concept. Yet, a bottom-up approach has not garnered much empirical interest, most likely because the requisite statistical models have not been available. The recently proposed model-based latent composite score can fill this gap. Therefore, we contrasted top-down and bottom-up representations of global self-concept by comparing conventional second-order factors and model-based latent composite scores. Across three independent large-scale studies (Study 1: N = 8,063; Study 2: N = 3,081; Study 3: N = 2,106), the second-order factors reproduced only small amounts of interindividual differences, which boosted the correlations with external criteria (i.e., self-esteem, enjoyment of school, academic outcomes) to theoretically and somewhat empirically implausible levels. By contrast, the composite score showed a more plausible pattern of stabilities and correlations. We discuss the consequences of the two approaches and propose the latent composite score as a new perspective on the apex of the Shavelson model.

2021 ◽  
Vol 14 (3) ◽  
pp. 354-391
Author(s):  
Richard Huyghe ◽  
Marine Wauquier

The formation of French agent nouns (ANs) involves a large variety of morphological constructions, and particularly of suffixes. In this study, we focus on the semantic counterpart of agentive suffix diversity and investigate whether the morphological variety of ANs correlates with different agentive subtypes. We adopt a distributional semantics approach and combine manual, computational and statistical analyses applied to French ANs ending in -aire, -ant, -eur, -ien, -ier and -iste. Our methodology allows for a large-scale study of ANs and involves both top-down and bottom-up procedures. We first characterize agentive suffixes with respect to their morphosemantic and distributional properties, outlining their specificities and similarities. Then we automatically cluster ANs into distributionally relevant subsets and examine their properties. Based on quantitative analysis, our study provides a new perspective on agentive suffix rivalry in French that both confirms existing claims and sheds light on previously unseen phenomena.


2016 ◽  
Vol 44 (4) ◽  
pp. 522-542 ◽  
Author(s):  
Christofer Berglund

After the Rose Revolution, President Saakashvili tried to move away from the exclusionary nationalism of the past, which had poisoned relations between Georgians and their Armenian and Azerbaijani compatriots. His government instead sought to foster an inclusionary nationalism, wherein belonging was contingent upon speaking the state language and all Georgian speakers, irrespective of origin, were to be equals. This article examines this nation-building project from a top-down and bottom-up lens. I first argue that state officials took rigorous steps to signal that Georgian-speaking minorities were part of the national fabric, but failed to abolish religious and historical barriers to their inclusion. I next utilize a large-scale, matched-guise experiment (n= 792) to explore if adolescent Georgians ostracize Georgian-speaking minorities or embrace them as their peers. I find that the upcoming generation of Georgians harbor attitudes in line with Saakashvili's language-centered nationalism, and that current Georgian nationalism therefore is more inclusionary than previous research, or Georgia's tumultuous past, would lead us to believe.


Author(s):  
Fred Young Phillips ◽  
LaVonne Reimer ◽  
Rebecca Turner

The latest IPCC report forcefully states that immediate, decisive, and large-scale actions are needed to avert climate catastrophe. This essay presumes that democratic governments are best and most desirably positioned to take these actions. Yet in the countries most pivotal to global climate, significant voting blocs are uninterested in environmental issues. The essay urges adding bottom-up dialog between environmental and anti-environmental voters, to current and future top-down technocratic “solutions.” To make this combination result in a unified pro-environment electorate, we must understand: religious objections to environmentalism; the capital-vs.-knowledge strife that slows polluting corporations’ green transitions; and the psychological mechanisms that can make inter-group dialog fruitful.


2016 ◽  
Author(s):  
Francesco Graziosi ◽  
Jgor Arduini ◽  
Paolo Bonasoni ◽  
Francesco Furlani ◽  
Umberto Giostra ◽  
...  

Abstract. Carbon tetrachloride (CCl4) is a long-lived radiatively-active compound able to destroy stratospheric ozone. Due to its inclusion in the Montreal Protocol on Substances that Deplete the Ozone Layer, the last two decades have seen a sharp decrease in its large scale emissive use with a consequent decline of its atmospheric mole fractions. However, the Montreal Protocol restrictions do not apply to the use of carbon tetrachloride as feedstock for the production of other chemicals, implying the risk of fugitive emissions from the industry sector. The occurrence of such unintended emissions is suggested by a significant discrepancy between global emissions as derived by reported production and feedstock usage (bottom-up emissions), and those based on atmospheric observations (top-down emissions). In order to better constrain the atmospheric budget of carbon tetrachloride, several studies based on a combination of atmospheric observations and inverse modelling have been conducted in recent years in various regions of the world. This study is focused on the European scale and based on long-term high-frequency observations at three European sites, combined with a Bayesian inversion methodology. We estimated that average European emissions for 2006–2014 were 2.3 (± 0.8) Gg yr−1, with an average decreasing trend of 7.3 % per year. Our analysis identified France as the main source of emissions over the whole study period, with an average contribution to total European emissions of 25 %. The inversion was also able to allow the localisation of emission "hot-spots" in the domain, with major source areas in Southern France, Central England (UK) and Benelux (Belgium, The Netherlands, Luxembourg), where most of industrial scale production of basic organic chemicals are located. According to our results, European emissions correspond to 4.0 % of global emissions for 2006–2012. Together with other regional studies, our results allow a better constraint of the global budget of carbon tetrachloride and a better quantification of the gap between top-down and bottom-up estimates.


2003 ◽  
Vol 12 (03) ◽  
pp. 227-248 ◽  
Author(s):  
Henning Christiansen ◽  
Veronica Dahl

We propose an abductive model based on Constraint Handling Rule Grammars (CHRGs) for detecting and correcting errors in problem domains that can be described in terms of strings of words accepted by a logic grammar. We provide a proof of concept for the specific problem of detecting and repairing natural language errors, in particular, those concerning feature agreement. Our methodology relies on grammar and string transformation in accordance with a user-defined dictionary of possible repairs. This transformation also serves as top-down guidance for our essentially bottom-up parser. With respect to previous approaches to error detection and repair, including those that also use constraints and/or abduction, our methodology is surprisingly simple while far-reaching and efficient.


RSC Advances ◽  
2016 ◽  
Vol 6 (51) ◽  
pp. 45923-45930 ◽  
Author(s):  
Peixun Fan ◽  
Minlin Zhong ◽  
Benfeng Bai ◽  
Guofan Jin ◽  
Hongjun Zhang

Large-scale and cost-effective generation of desired 3D self-supporting macro–micronano-nanowire architectures is realized by a top-down and bottom-up combined approach.


2001 ◽  
Vol 1 (Special) ◽  
pp. 82-95
Author(s):  
A.S. Dzurak ◽  
M.Y. Simmons ◽  
A.R. Hamilton ◽  
R.G. Clark ◽  
R. Brenner ◽  
...  

We discuss progress towards the fabrication and demonstration of a prototype silicon-based quantum computer. The devices are based on a precise array of 31P dopants embedded in 28Si. Fabrication is being pursued via two complementary pathways – a ‘top-down’ approach for near-term production of few-qubit demonstration devices and a ‘bottom-up’ approach for large-scale qubit arrays. The ‘top-down’ approach employs ion implantation through a multi-layer resist structure which serves to accurately register the donors to metal control gates and single-electron transistor (SET) read-out devices. In contrast the ‘bottom-up’ approach uses STM lithography and epitaxial silicon overgrowth to construct devices at an atomic scale. Techniques for qubit read-out, which utilise coincidence measurements on novel twin-SET devices, are also presented.


Author(s):  
SUNGHO KIM ◽  
GIJEONG JANG ◽  
WANG-HEON LEE ◽  
IN SO KWEON

This paper presents a combined model-based 3D object recognition method motivated by the robust properties of human vision. The human visual system (HVS) is very efficient and robust in identifying and grabbing objects, in part because of its properties of visual attention, contrast mechanism, feature binding, multiresolution and part-based representation. In addition, the HVS combines bottom-up and top-down information effectively using combined model representation. We propose a method for integrating these aspects under a Monte Carlo method. In this scheme, object recognition is regarded as a parameter optimization problem. The bottom-up process initializes parameters, and the top-down process optimizes them. Experimental results show that the proposed recognition model is feasible for 3D object identification and pose estimation.


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