Core Assumptions Research Articles

Theories of Uncertainty Communication: An Interdisciplinary Literature Review

This systematic literature review presents an interdisciplinary overview of theories tested in experiments on the effects of communicating uncertainty. Using a machine learning-aided pipeline, we selected and manually coded 413 experimental studies. We discuss core assumptions and predictions of the main theories of uncertainty communication. Most normative theorizing (e.g., Bayesianism, Expected Utility Theory) is rooted in Probability Theory, which is only suitable for addressing shallow and medium uncertainty. This explains the underrepresentation of experimental research into deep uncertainty communication. To foster a more comprehensive understanding of uncertainty communication effects, we identify research questions and theories deserving greater attention.

A set-analytic approach to intersectionality

In this paper, we propose a set-analytic approach to the study of intersectionality. Our approach builds on the intersectional view that combinations of attributes, such as black females, should be understood as qualitatively distinct states, not reducible to their component attributes. We show that interaction-based, quantitative approaches are not only inconsistent with the core assumptions of intersectionality but also may underestimate the presence of penalties linked to multi-category memberships. In contrast, we show that truth table analysis, a core feature of Qualitative Comparative Analysis, directly implements several of the core methodological concerns of the intersectionality perspective. The truth table approach offers two important advantages. (1) It provides a foundation for the comparison of logically ‘adjacent’ configurations—combinations of case characteristics that differ by only a single attribute. (2) It can accommodate case attributes that vary by level or degree in a set-theoretic, intersectional framework.

Anger has benefits for attaining goals.

[Correction Notice: An Erratum for this article was reported in Vol 126(4) of Journal of Personality and Social Psychology (see record 2024-93961-001). In the article (https://doi.org/10.1037/pspa 0000350), the first paragraph in the Method section of Study 4 has been revised. All paragraphs in the Results section of Study 4 have been revised. Table 1 and Figure 5 have been updated. All versions of this article have been corrected.] Functional accounts of emotion have guided research for decades, with the core assumption that emotions are functional-they improve outcomes for people. Based on functional accounts of emotion, we theorized that anger should improve goal attainment in the presence of challenges. In seven studies, goal attainment was assessed in situations that involved varying levels of challenges to goal attainment. Across studies, anger compared to a neutral condition resulted in behavior that facilitated greater goal attainment on tasks that involved challenges. With a goal to solve difficult puzzles, anger resulted in more puzzles correctly solved (Study 1). With a goal to attain prizes, anger increased cheating rates and numbers of unearned prizes (Study 2). With a goal to do well in a video game, anger increased scores on a game with challenges to be avoided, but not other scores (Study 3). In two studies, examining the consequences of anger in response to the challenging task that was the focus of that anger, anger decreased reaction time with goals to win trials (Study 4), and predicted making the effort to vote in two contentious elections (Study 5). With a goal to protect financial resources, anger increased action taken to prevent loss compared to a physiological arousal condition (Study 6). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

Correction to "Anger has benefits for attaining goals" by Lench et al. (2023).

Reports an error in "Anger has benefits for attaining goals" by Heather C. Lench, Noah T. Reed, Tiffany George, Kaitlyn A. Kaiser and Sophia G. North (Journal of Personality and Social Psychology, Advanced Online Publication, Oct 30, 2023, np). In the article (https://doi.org/10.1037/pspa 0000350), the first paragraph in the Method section of Study 4 has been revised. All paragraphs in the Results section of Study 4 have been revised. Table 1 and Figure 5 have been updated. All versions of this article have been corrected. (The following abstract of the original article appeared in record 2024-17814-001.) Functional accounts of emotion have guided research for decades, with the core assumption that emotions are functional-they improve outcomes for people. Based on functional accounts of emotion, we theorized that anger should improve goal attainment in the presence of challenges. In seven studies, goal attainment was assessed in situations that involved varying levels of challenges to goal attainment. Across studies, anger compared to a neutral condition resulted in behavior that facilitated greater goal attainment on tasks that involved challenges. With a goal to solve difficult puzzles, anger resulted in more puzzles correctly solved (Study 1). With a goal to attain prizes, anger increased cheating rates and numbers of unearned prizes (Study 2). With a goal to do well in a video game, anger increased scores on a game with challenges to be avoided, but not other scores (Study 3). In two studies, examining the consequences of anger in response to the challenging task that was the focus of that anger, anger decreased reaction time with goals to win trials (Study 4), and predicted making the effort to vote in two contentious elections (Study 5). With a goal to protect financial resources, anger increased action taken to prevent loss compared to a physiological arousal condition (Study 6). (PsycInfo Database Record (c) 2024 APA, all rights reserved).

A comparison of four self-controlled study designs in an analysis of COVID-19 vaccines and myocarditis using five European databases

IntroductionThe aim of this study was to assess the possible extent of bias due to violation of a core assumption (event-dependent exposures) when using self-controlled designs to analyse the association between COVID-19 vaccines and myocarditis. MethodsWe used data from five European databases (Spain: BIFAP, FISABIO VID, and SIDIAP; Italy: ARS-Tuscany; England: CPRD Aurum) converted to the ConcePTION Common Data Model. Individuals who experienced both myocarditis and were vaccinated against COVID-19 between 1 September 2020 and the end of data availability in each country were included. We compared a self-controlled risk interval study (SCRI) using a pre-vaccination control window, an SCRI using a post-vaccination control window, a standard SCCS and an extension of the SCCS designed to handle violations of the assumption of event-dependent exposures. ResultsWe included 1,757 cases of myocarditis. For analyses of the first dose of the Pfizer vaccine, to which all databases contributed information, we found results consistent with a null effect in both of the SCRI and extended SCCS, but some indication of a harmful effect in a standard SCCS. For the second dose, we found evidence of a harmful association for all study designs, with relatively similar effect sizes (SCRI pre = 1.99, 1.40 – 2.82; SCRI post 2.13, 95 %CI – 1.43, 3.18; standard SCCS 1.79, 95 %CI 1.31 – 2.44, extended SCCS 1.52, 95 %CI = 1.08 – 2.15). Adjustment for calendar time did not change these conclusions. Findings using all designs were also consistent with a harmful effect following a second dose of the Moderna vaccine. ConclusionsIn the context of the known association between COVID-19 vaccines and myocarditis, we have demonstrated that two forms of SCRI and two forms of SCCS led to largely comparable results, possibly because of limited violation of the assumption of event-dependent exposures.

Learning manifolds from non-stationary streams

Streaming adaptations of manifold learning based dimensionality reduction methods, such as Isomap, are based on the assumption that a small initial batch of observations is enough for exact learning of the manifold, while remaining streaming data instances can be cheaply mapped to this manifold. However, there are no theoretical results to show that this core assumption is valid. Moreover, such methods typically assume that the underlying data distribution is stationary and are not equipped to detect, or handle, sudden changes or gradual drifts in the distribution that may occur when the data is streaming. We present theoretical results to show that the quality of a manifold asymptotically converges as the size of data increases. We then show that a Gaussian Process Regression (GPR) model, that uses a manifold-specific kernel function and is trained on an initial batch of sufficient size, can closely approximate the state-of-art streaming Isomap algorithms, and the predictive variance obtained from the GPR prediction can be employed as an effective detector of changes in the underlying data distribution. Results on several synthetic and real data sets show that the resulting algorithm can effectively learn lower dimensional representation of high dimensional data in a streaming setting, while identifying shifts in the generative distribution. For instance, key findings on a Gas sensor array data set show that our method can detect changes in the underlying data stream, triggered due to real-world factors, such as introduction of a new gas in the system, while efficiently mapping data on a low-dimensional manifold.

Generalized time-bin quantum random number generator with uncharacterized devices

Random number generators (RNG) based on quantum mechanics are captivating due to their security and unpredictability compared to conventional generators, such as pseudo-random number generators and hardware-random number generators. This work analyzes evolutions in the extractable amount of randomness with increasing the Hilbert space dimension, state preparation subspace, or measurement subspace in a class of semi-device-independent quantum-RNG, where bounding the states’ overlap is the core assumption, built on the prepare-and-measure scheme. We further discuss the effect of these factors on the complexity and draw a conclusion on the optimal scenario. We investigate the generic case of time-bin encoding scheme, define various input (state preparation) and outcome (measurement) subspaces, and discuss the optimal scenarios to obtain maximum entropy. Several input designs were experimentally tested and analyzed for their conceivable outcome arrangements. We evaluated their performance by considering the device’s imperfections, particularly the after-pulsing effect and dark counts of the detectors. Finally, we demonstrate that this approach can boost the system entropy, resulting in more extractable randomness.

Multiscale-based multiaxial fatigue model of short fiber reinforced polymer composites under high-cycle proportional loading

Due to the inhomogeneity and anisotropy of short fiber-reinforced polymers (SFRP), even uniaxial loading can induce multiaxial stress states inside them, which significantly increases the difficulty of grasping their fatigue behavior. To efficiently predict the fatigue life of SFRP under proportional multiaxial stress, a multiaxial high-cycle fatigue model is proposed, relying upon the multiscale modeling strategy capable of integrating the influence of fiber microstructure. Taking the fiber-matrix interface stress at the critical region as the internal driving factor of fatigue fracture is the core assumption verified by microscopic observations. Off-axial fatigue tests with different orientations and stress ratios are performed to validate the fatigue model. Results show that the prediction accuracy has reached an acceptable level, and the quadratic polynomial surface can well represent the relationship between fatigue life and multiaxial stresses. This work provides an efficient tool for multiaxial fatigue life prediction and expounds the failure behavior of SFRP from multiscale perspectives.

Political Business Cycles in Türkiye: A Chaotic Perspective

AbstractThis paper has the goal of analyzing the chaotic structure of political business cycles in Türkiye for the period from 1986 March to 2020 January. To investigate the existence of uncertainty, the chaotic dynamics of the analyzed variables was examined using the Lyapunov exponent, Shannon entropy, and Hurst entropy. The Fourier VAR model was applied to determine the effects of unemployment, inflation, economic growth, and the minimum wage on voting behavior in Türkiye. The Granger Causality approach was also used to assess the direction of the causal relationship between macroeconomic factors and political party groups. Granger causality analysis findings of this paper reveal a bi-directional Granger causality link between the center-right party and economic growth, inflation, unemployment, and the minimum wage. Furthermore, there is also a uni-directional causality relation from inflation, unemployment, and economic growth to the center-left party and a bi-directional causality relation between the minimum wage and the center-left party. In this regard, one of the most remarkable evaluations of this paper is that the sensitivity findings of party groups to macroeconomic factors in Türkiye do not align with the core assumptions of the Partisan Theory concerning the right-left party division. Therefore, contrary to the related theory, the analysis results indicate that it is not eligible to make a sharp and distinct distinction between right-wing and left-wing parties in Türkiye. Additionally, Lyapunov exponent, Shannon entropy, and Hurst entropy findings point to the existence of chaotic structure and uncertainty in political cyclical fluctuations in Türkiye. Accordingly, it is figured out that the existence of chaotic structure and uncertainty in party groups and analyzed variables allows only short-term and not long-term forecasting.

Advocacy coalitions as political organizations

Abstract Conceptually, advocacy coalitions are referenced in several policy process theories and frameworks to describe groups of actors that share beliefs and coordinate efforts to influence public policy. In the past decades, advocacy coalitions have received increased attention as a concept and a theoretical approach to understanding collective action in the policy process. In this study, we argue that despite its growing popularity, past empirical research has mainly focused on identifying and describing advocacy coalitions while largely overlooking their role and impact as political organizations. Many of the core premises and assumptions about advocacy coalitions hereby remain understudied and untested. Here, we depart from the Advocacy Coalition Framework (ACF) to discuss the political organization of advocacy coalitions by focusing on four dimensions: (1) a basis for engagement in joint strategies, (2) capacity to mobilize political resources, (3) ability to gain influence in policy processes, and (4) perceptions of advocacy coalitions as a political entity. We briefly review the theory and evidence of each dimension and conclude that several core assumptions about advocacy coalitions yet remain to be empirically tested to enable further conceptual specification and theory development within the ACF and beyond. To this end, we propose a research agenda with suggested research questions, designs, and methodological considerations for advancing empirical research on the role and impact of advocacy coalitions in different cases and contexts.

Blinded by “algo economicus”: Reflecting on the assumptions of algorithmic management research to move forward

AbstractThis paper reflects on the paradigmatic assumptions and ideologies that have shaped algorithmic management research. We identify two sets of assumptions: one about the “ontology of algorithms” (which holds that human resource management [HRM] algorithms are non‐human entities with material agency) and one about the “ontology of management” that HRM algorithms afford (which understands algorithmic management as a form of control for maximizing economic/shareholder value). We explain how these core assumptions underpin existing research of HRM algorithms, causing blind spots that hinder new ways of understanding and studying algorithmic management. After identifying and unpacking the assumptions and blind spots, we offer avenues to overcome these blind spots, allowing for future research based on new ideological assumption grounds that will help move algorithmic management scholarship further in significant ways.

When procedures and ideology replace strategy in corporate political activity: Industry associations in Interwar Finland

The core assumption in the management literature on corporate political activity (CPA) is that firms and industry associations representing their interests seek political ends driven by strategic concerns. Other streams of research, however, emphasise the role of ideology in CPA. In this article, we study the balance between strategic and ideological orientations over time. We draw on historical data from the early 1920s to the end of the 1930s to analyse a process in which two competing Finnish industry associations sought to balance strategic and ideological CPA, and how procedural CPA became increasingly important as a mechanism for increasing the emphasis on ideological goals. As industry associations become more autonomous, they gain more opportunities and greater power. As a result of this increased power, associations can promote their own ideological agendas, which often contrast with what would be directly beneficial for individual firms and societies.

Meta-theorizing framing in communication research (1992–2022): toward academic silos or professionalized specialization?

Abstract Framing, a prominent communication theory, is often lamented as a fractured paradigm, leading some to offer radical changes to its conceptualization, operationalization, and application. Using a meta-theoretical and computational approach, we analyze three decades of framing research to examine academic silos, specializations, the canon’s formation, gender inequalities, authors’ origins, countries studied, and methods used in framing research. Instead of silos, our analysis of 5,291 papers and over 170,000 citations identified specializations formed around a core of canonic texts. While framing research has become more diverse over the years, males affiliated with U.S. institutions still predominately author canonical works. Results reject the isolated-silos hypothesis in favor of a view of framing as a bridging networked paradigm, coalescing around core assumptions, definitions, and approaches. These findings contrast with the common fractured-paradigm narrative and challenge calls for radical solutions.

Revisiting ‘Accuracy’ in Formal Grounded Theory: Ambiguities and Opportunities

This study attempts to address the ‘scant attention’ (to use Barney Glaser’s words) given to formal grounded theory by revisiting and reformulating the concept of accuracy (interchangeably used with accurate descriptions and empirical evidence) which Glaser blames to be the reason behind grounded theorists neglecting formal grounded theorizing. A novel concept called pragmatic accuracy is introduced to meet the requirements of formal grounded theorizing. Pragmatic accuracy by supplementing inductive reasoning with abductive places methodological self-consciousness at the center of formal grounded theorizing as there is a continual need for scrutinizing the core assumptions of a researcher and those of their participants’. This study does not entirely reject Glaser’s approach of shunning accuracy. Rather it teases out the contradiction between Glaser’s words and practice towards qualitative descriptions and shows how he, in a coauthored formal grounded theory, recognizes the importance of empirical references and explanatory definitions. Along with Glaser, Charmaz’ and Kearney’s views on accuracy are also unpacked and brought in harmony with the requirements of formal grounded theorizing. A case is made through pragmatic accuracy to encourage a sustained focus on the inclusion of empirical content in an emerging formal theory to increase its applicability and generalizability. The reformulated pragmatic accuracy also offers two lengths for formal grounded theories, article-length and book-length, depending upon the requirements of the topic and the researcher.

"Will the welfare state survive the future? - How people legitimize the welfare state."

Background: Legitimacy of the welfare state is a requirement for efficient functioning. In the current political climate of Norway creating new co-governance models under the umbrella of New Public Governance (NPG). NPG draws resources from the public, the private as well as the volunteer sector. In the European welfare states pressure is building due to demographic ageing, globalization and disturbances in the social order which affect the social contract between citizen and state. This article aims to explore how citizens legitimize the Norwegian welfare state drawing on perspective of institutional theory. Why do or don’t the participants support the current form of the welfare state?
 The interviews were analysed focusing on the assumptions and reasons on which the participants based their view of the welfare state. Although the method has been used on exploring the epistemic dimension of discretion, it allows for identification of the cognitive aspects of decision making, hence the ability to identify core assumptions and beliefs. The findings from the interview are analysed using Schuman’s analytical categories of pragmatic, moral and cognitive legitimacy create the framework for analysing the argumentation which the participants use to legitimize their current view of the Norwegian welfare state, and where it is heading. Contrary to most institutional research this paper does not attempt to see the big picture, but rather explore legitimacy through the informant’s perception of the welfare state.
 Methods: This is a qualitative study. We conducted individual interviews with one woman and one man in each 10-year, thus representing ages from 20 to 80. We also interviewed two senior experts at research centres and two politicians. These interviews were thematically analysed and coded in NVivo.
 In order to analyse the informant’s arguments further this paper utilizes Anders Molander’s interpretation and use of Toulmin which sees discretion as a process in which a person legitimizes their own argument statements through expressing core concepts, values and understandings.
 Results and Lessons learned: This is an ongoing study and the results will be presented and discussed at the conference. The preliminary analysis shows that moral legitimacy tends to outweigh pragmatic legitimacy. This implies that legitimacy is a key concept in achieving integrated services. This may indicate that cooperative models such as NPG in combination with people’s perspective of “what is the right thing to do” is key to reaching ideals promised in tailoring of services from people’s perspective.
 
 
 Limitations and suggestions for future research: Legitimacy as a concept on the micro level may be a key element in understanding how to integrate services and increase quality of services from people’s perspective. Moral legitimacy tends to create support despite to achieving peoples wishes. To a certain extent, the upcoming results will be of relevance for a better understanding of the complexity of organising and supporting welfare services. 
 Keywords: Welfare state, legitimacy, NPG, Co-governance, integration, 

High school students' evolving alternative conception related to the volume of gas: A Lakatosian perspective

AbstractThe purpose of this case study, informed by a Lakatosian perspective, is to identify how an alternative conception that originates in present learning but is related directly to subsequent learning contexts can be constructed. Before the study, one of the authors found by accident that a student who had learned about Avogadro's principle and chemical reaction in South Korea constructed an alternative conception related to the volume of gas. Later, we identified seven Korean high school students with the alternative conception through a test and analyzed their underlying understandings qualitatively through interviews. The results show that they had a scientific conception—core conception—and intuitive assumptions about implicit information of external representations—implicit assumptions—in common. The students' implicit assumptions could be divided into three types again: core assumption, auxiliary assumption, and context‐inducing assumption. The core assumption, like the core conception, played a significant role in constructing the alternative conception (hard core), while the auxiliary assumptions were incomplete implicit assumptions to protect the alternative conception (protective belt). The context‐inducing assumption was an implicit assumption bringing the context of the subsequent curriculum, and the core conception and the core assumption could be interpreted in this induced context. At the end of the study, the implications related to learning progressions were discussed.

Shallow fixes and deep reasonings: framing sustainability at the Brazilian Agricultural Research Corporation (Embrapa)

The need for urgent, structural transformations to dominant food systems is increasingly recognized in research and policy. The direction these transformations take is in great part influenced by how the problem is framed and what future pathways become seen as plausible and desirable. Scientific knowledge and the organizations producing it hold considerable authority in suggesting what alternatives are or are not worth pursuing, ultimately shaping frames and in turn being shaped by them. This paper examines Brazil’s federal Agricultural Research Corporation (Embrapa), a major contributor to technological advances that made Brazil into an agricultural powerhouse. We examine the ways in which Embrapa’s leadership has framed sustainable agriculture in its public communication and the wider implications for food systems transformation. Drawing from Embrapa news articles in the period 2015–2020, we identify four interrelated frames forming Embrapa’s prevalent position on sustainability. Our results show that while Embrapa promotes practices based on alternative approaches such as agroecology, its deeper framing often reflects the core assumptions driving dominant industrial food systems. This framing reinforces underlying logics of control, efficiency, and competition aligned with the productivist paradigm and excludes divergent perspectives that exist within the organization.

Abstract IA034: Incorporating intersectionality in quantitative cancer disparities research

Abstract Intersectionality is a framework that posits individuals have multiple interacting social identities, both at the individual and structural level, that mediate both privilege and oppression. In the past decade, researchers have increasingly adopted intersectionality as a conceptual framework to study whether and how social identities influence health disparities. While individual and socio-contextual cancer disparities have been widely demonstrated across the cancer continuum (from prevention to survivorship), it is unknown the extent to which intersectionality as a framework, including its core assumptions and components, have been applied to this field of study. In this study, using PRISMA guidelines, we conducted a systematic review of quantitative cancer disparity studies that explicitly cited intersectionality as a guiding approach to their study. Results presented will narratively synthesize the identified literature to identify challenges, gaps, and recommendations for incorporating intersectionality theory into quantitative cancer disparity research. Citation Format: Priti Bandi, Kilan C. Ashad-Bishop. Incorporating intersectionality in quantitative cancer disparities research [abstract]. In: Proceedings of the 16th AACR Conference on the Science of Cancer Health Disparities in Racial/Ethnic Minorities and the Medically Underserved; 2023 Sep 29-Oct 2;Orlando, FL. Philadelphia (PA): AACR; Cancer Epidemiol Biomarkers Prev 2023;32(12 Suppl):Abstract nr IA034.

Emosjonsfokusert terapi

Emotion-Focused Therapy (EFT) is rooted in the humanistic psychotherapy tradition. A core assumption in EFT is that our life experiences are organised in emotion schemes. For instance, problematic childhood experiences that are not processed can form what are typically referred to as maladaptive emotion schemes, continuing to influence us later in in life. The goal in EFT is to activate, process and change maladaptive emotion schemes. Such a change process typically occurs through an emotional sequence, moving from secondary emotions (e.g., depressive hopelessness) through primary maladaptive emotions (e.g., maladaptive shame) to adaptive emotions (e.g., assertive anger). This sequence is termed changing emotion with emotion, and builds on substantial process research. In this article, we will describe from an EFT perspective how psychological illness arises and which conditions are necessary for it to change. We will give an account of the empirical foundation for the model and illustrate some specific interventions using the case of ‘Nadine’. Keywords: Emotion-Focused Therapy, transdiagnostic therapy, humanistic therapy, experiential therapy

Policy complementarity and the paradox of carbon pricing

AbstractWe present an economics framework appropriate to the exceptionally broad scope of the climate change problem. This considers that economic and social processes, particularly those involved in purposive transitions of energy technologies and systems, involve the interplay between three distinct domains of decision-making and associated actors. The first concerns small-scale and often short-term decision-making, much of which reflects extensive ‘satisficing’ and habituation as identified in behavioural economics. Calculated economic optimization decisions, especially of companies in the energy and energy-intensive industries, then best reflect the core assumptions of neoclassical and welfare economics, including discrete market failures. Third, at the largest scale are strategic judgements made by big actors (e.g. governments, large multinational companies) relevant to transformation of complex systems over long periods—particularly concerning innovation and structural changes, for which lessons from theories of evolutionary and institutional economics are most relevant.Economically, these can be logically mapped in relation to the technology (or more accurately, ‘best practice’) frontier. Each has corresponding policy implications: most directly, respectively in terms of (i) standards and engagement to establish norms; (ii) competitive markets with the critical role of prices; and (iii) strategic investment in innovation and infrastructure. Each faces challenges of implementation and government failure, as observed, for example, with wholly inadequate carbon pricing to date, naïve and ineffective approaches to enhancing energy efficiency, or misdirected support to R&D. Based on the domain distinctions, we argue that the corresponding pillars of policy are naturally complementary, and can be mutually supportive: strong standards and norms on energy efficiency, for example, would enhance the political space for carbon pricing by reducing its direct consumer impacts, while carbon pricing has multiple positive two-way interactions with enhanced low-carbon innovation.From this we also posit a ‘carbon pricing paradox’: that adequate carbon prices, the central recommendation of most economists, are in most jurisdictions only feasible (or even optimal) if equal analytic and policy attention is devoted to the other pillars, and the wider context of macroeconomic and fiscal policies. Only these other aspects can reduce the absolute cost impact of carbon pricing (potentially turning into a gain) and offer consumers and businesses better lower-carbon alternatives, which are critical to establishing climate-compatible pricing structures across our economies.