Empirical Problems Research Articles

From Empirical Problem-Solving to Theoretical Problem-Finding Perspectives on the Cognitive Sciences

AbstractMeta-theoretical perspectives on the research problems and activities of (cognitive) scientists often emphasize empirical problems and problem-solving as the main aspects that account for scientific progress. While certainly useful to shed light on issues of theory-observation relationships, these conceptual analyses typically begin when empirical problems are already there for researchers to solve. As a result, the role of theoretical problems and problem-finding remain comparatively obscure. How do the scientific problems of Cognitive Science arise, and what do they comprise, empirically and theoretically? Here, we attempt to understand the research activities that lead to adequate explanations through a broader conception of the problems researchers must attend to and how they come about. To this end, we bring theoretical problems and problem-finding out of obscurity to paint a more integrative picture of how these complement empirical problems and problem-solving to advance cognitive science.

Changes of Organizational Culture at the Public Health Center in Cilincing District, North Jakarta, Indonesia

The empirical problem in this research is that in the working area of the Cilincing District Public Health Center, they have never carried out health education or monitoring activities in fisheries areas, including how to make salted fish. The study aims (1) to measure responsive culture, awareness management, organizational commitment, and identification of formalin in salted fish before and after implementing responsive culture. Furthermore, the study analyzes the influence of awareness management and organizational commitment on responsive culture and formalization in salted fish. It also aims to determine the best influence path model. The design used is to provide a responsive culture module and pre-post observational. Descriptive analysis was used to determine the distribution of respondents regarding responsive culture; awareness management; organizational commitment; and identification of formalin in salted fish. SEM SmartPLS is used to test the influence between variables. The results showed that the best model of influence path is (1) awareness management has a direct effect on organizational commitment; (2) organizational commitment influences responsive culture and responsive culture influences formalin content in salted fish. It is proven that a responsive culture plays an important role in overcoming health center performance problems. After implementing the responsive culture module, and a formalin test was carried out on making salted fish, the results showed that there was no formaline in salted fish.

Между имперским и постимперским дискурсом: идеи империи и революции в оптике исследователей XXI века (Рец. на: Идея империи и идея революции в русской философии и культуре XIX–XX веков: коллективная монография / отв. ред. И.И. Евлампиев. СПб.: Изд-во РХГА, 2023. 420 с.)

The paper analyses the collective monograph: “The Idea of Empire and the Idea of Revolution in Russian Philosophy and Culture of the XIX–XX Centuries”, its content being a reflection on one of the most intellectually acute and complex contradictions of Russian history – the problem of empire and revolution. This problem invariably awakens philosophical thought, forcing it to search for an explanation of the notorious “pendulum of Russian history”, the genesis of power, the vector and track of Russian history, which are intellectual outgrowths of the fundamental problem – the problem of Russian civilizational and state identity. The content of the work is an analysis of empire and revolution – the main concepts that are in the focus of philosophical interest and reflection in Russian culture of the XIX–XX centuries. Its aim is to demonstrate the theoretical demand to continue the analysis and philosophical reflection of the concepts of empire and revolution, with the task of rethinking and reinterpreting them. The thesis is presented about the inexhaustibly traditional historical-philosophical narrative (liberalism-conservatism) and the discursively traditional nature of the range of topics, problems and questions, centred on the concepts of “empire” and “revolution”, with the same inexhaustibly traditional duality of interpretation (“us–them”, “East–West”). The result of the analysis of the sections that make up the content of the monograph is the conclusion about the epistemological and axiological value of the concepts of empire and revolution, and the heuristic productivity of the works related to their analysis in the context of the challenges faced by the Russian society and state. The latter can be used as analytical tools for works that develop and deepen the problems of empire and revolution on a modern historiographical basis. The historiographical basis of the article is the works of well-known Russian and foreign authors specializing in this field of humanities, and the methodological basis is hermeneutic analysis with the involvement of the discourse of cultural studies, political science and history.

ETHICAL AND AXIOLOGICAL ASPECT OF PROFESSIONAL TRAINING OF MASTERS IN THE HUMANITIES

The article investigates the topical scientific and empirical problem of professional training of masters in the humanities at Ukrainian universities based on cultural, personal, and integration paradigms with the use of methodological and technological tools of historical, pedagogical, and modern scientific approaches. The models and factors of training masters in the humanities at universities throughout the entire period of existence of these institutions are generalized; the concept and contextual and professional model of the system of such training on axiological principles are presented. As a result of a gradual elucidation of the prerequisites and factors of the value dimension of humanitarian education of masters in different models of European universities for the period from the time of their emergence (the lower boundary of the study is the IX century) to the present (the beginning of the XXI century), the essence of the concept of «axisphere of future masters in the humanities» (a set of values of the personality of specialists that determine their activity in teaching and research) is clarified. Their attitude to the world and their self-knowledge in the chosen field and specialty is clarified using analytical and methodological tools of historical and pedagogical general scientific and special pedagogical approaches; the need to develop and implement in practice the educational and research activities of modern universities of the humanities is explained. The technological and methodological support of the proposed model is updated. It is proved that the tendencies of internationalization, intensification, deepening of international cooperation, and building a context-oriented environment for training masters in the humanities in modern universities based on an integrative educational paradigm contribute to a powerful renewal of teaching, research, and provision of educational services; the values of multiculturalism of the personality of higher education students are determined as significant in the interdisciplinary scientific discourse (philosophy of education, sociology, psychology, pedagogy and education sciences, etc.) It is concluded that the main results of the study should be used for the further development of the system of professional training of masters in the humanities (historians, philosophers, religious studies, cultural studies, philology) on axiological principles in Ukrainian universities.

The strategic allocation theory of vigilance.

Despite its importance in different occupational and everyday contexts, vigilance, typically defined as the capacity to sustain attention over time, is remarkably limited. What explains these limits? Two theories have been proposed. The Overload Theory states that being vigilant consumes limited information-processing resources; when depleted, task performance degrades. The Underload Theory states that motivation to perform vigilance tasks declines over time, thereby prompting attentional shifts and hindering performance. We highlight some conceptual and empirical problems for both theories and propose an alternative: the Strategic Allocation Theory. For the Strategic Allocation Theory, performance on vigilance tasks optimizes as a function of intrinsic and extrinsic motivations, including metacognitive factors such as the expected value of effort and the expected value of planning. Limited capacities must be deployed across task sets to maximize expected reward. The observed limits of vigilance reflect changes in the perceived value of, among other things, sustaining attention to a task rather than attending to something else. Drawing from recent computational theories of cognitive control and meta-reasoning, we argue that the Strategic Allocation Theory explains more phenomena related to vigilance behavior than other theories, including self-report data. Finally, we outline some of the testable predictions the theory makes across several experimental paradigms. This article is categorized under: Philosophy > Foundations of Cognitive Science Psychology > Attention.

Bargaining on price on behalf of price-insensitive downstream consumers

There are settings in which prices are negotiated by procurement agents and final consumption decisions are made by end users who are indifferent to negotiated prices. For example, a patient seeking medical treatment is indifferent to the treatment's cost if it is covered by his insurance program. We study bargaining for per-unit prices between suppliers and an intermediary who represents price-insensitive consumers. Under the commonly used simultaneous bargaining framework we show that, if suppliers have sufficiently high bargaining power, the resulting prices will exceed the value of the good (or service) being delivered. This overpricing is solved if simultaneous negotiations are replaced by sequential ones. The theoretical problem with sequential negotiations is that they necessitate treating the suppliers asymmetrically, even if they are symmetric; the empirical problem with sequential negotiations is that the negotiations-order is unobservable. We propose a multi-period model that resolves these issues: overpricing is prevented and all suppliers are treated the same. In this model, the result about sequential negotiations is utilized in order to produce (asymmetric) off-path threats. These threats sustain symmetric on-path play.

Weakly Supervised AUC Optimization: A Unified Partial AUC Approach.

Since acquiring perfect supervision is usually difficult, real-world machine learning tasks often confront inaccurate, incomplete, or inexact supervision, collectively referred to as weak supervision. In this work, we present WSAUC, a unified framework for weakly supervised AUC optimization problems, which covers noisy label learning, positive-unlabeled learning, multi-instance learning, and semi-supervised learning scenarios. Within the WSAUC framework, we first frame the AUC optimization problems in various weakly supervised scenarios as a common formulation of minimizing the AUC risk on contaminated sets, and demonstrate that the empirical risk minimization problems are consistent with the true AUC. Then, we introduce a new type of partial AUC, specifically, the reversed partial AUC (rpAUC), which serves as a robust training objective for AUC maximization in the presence of contaminated labels. WSAUC offers a universal solution for AUC optimization in various weakly supervised scenarios by maximizing the empirical rpAUC. Theoretical and experimental results under multiple settings support the effectiveness of WSAUC on a range of weakly supervised AUC optimization tasks.

The problem of tropospheric temperature trend measurements for global climate models: Complex versus direct empiricism

The troposphere temperature controversy concerns an empirical problem facing global climate models (GCMs), that the (tropical) troposphere is not warming as fast as predicted by these models according to observations made by a group of climate scientists – John Christy and colleagues – located at the University of Alabama Huntsville (UAH). Elizabeth Lloyd argues that the UAH data, which conflict with GCM predictions, have been definitively discredited by a competing group of climate scientists, Ben Santer and colleagues, in a paper written in 2008. She also argues that Christy and colleagues make fundamental philosophical errors that undermine their empirical results. I argue that Lloyd's criticism is mistaken, both in terms of her assessment of the scientific value of the UAH data and in terms of her philosophical assessment of the reasoning Christy and colleagues use in support of this data. Contrary to Lloyd's assessment, Santor and colleagues have not definitively repudiated the UAH data, nor do they claim as such. Moreover, she misconstrues Christy and colleagues as philosophically committed to a direct empiricist viewpoint. As a result, I claim that the troposphere temperature controversy remains unsolved and continues to pose a potential problem for contemporary GCMs.

Nonparametric Approaches to Empirical Welfare Analysis

Welfare analysis of policy interventions is ubiquitous in economic research. It plays an important role in merger analysis and antitrust litigation, design of tax and subsidies, and informs the current debate on a universal basic income. This paper provides a survey of existing empirical methods, based on cross-sectional microdata, for calculating welfare effects and deadweight loss resulting from realized or hypothetical policy change. We briefly outline classical parametric methods that are computationally tractable, then discuss recent nonparametric approaches that avoid making statistical and functional-form restrictions on individual preferences. This makes the welfare estimates theoretically more credible, and clarifies exactly what welfare-relevant information is contained in demand distribution in various choice settings. However, these methods also demand greater in-sample variation in the data for practical implementation than classical parametric approaches. We then cover settings with externalities. The above results are theoretical, and take the demand function as known; therefore, we briefly discuss empirical problems around demand estimation. We conclude by suggesting areas for future research. (JEL C14, C35, D11, D60, D62)

Rule ordering is free: A case study of extraction out of ellipsis

This paper examines Bošković’s (2014) idea that extraction out of an ellipsis site is impossible when a phase is elided. One of the empirical problems with this analysis is that there is a case, pointed out in Takahashi (2020), where focus movement out of an elided CP (a phase) is possible in Japanese. By reformulating Bošković’s (2014) system in terms of Obata, Epstein and Baptista’s (2015) view that that ordering of rule-application is underspecified in UG, we demonstrate that the ordering between Internal Merge (IM) and Bošković’s ‘Marking for Ellipsis’ (ME) is crucial: in Bošković’s system, ME needs to precede IM, which makes extraction out of CP impossible. If IM precedes ME, on the other hand, extraction out of CP should be equally possible, which enables us to generate Takahashi’s (2020) focus movement case. As a consequence, our analysis clarifies what roles labels play in the interfaces, which supports Chomsky’s (2013) view that labels are necessary for interface interpretation.

On the convergence of gradient descent for robust functional linear regression

Functional data analysis offers a set of statistical methods concerned with extracting insights from intrinsically infinite-dimensional data and has attracted considerable amount of attentions in the past few decades. In this paper, we study robust functional linear regression model with a scalar response and a functional predictor in the framework of reproducing kernel Hilbert spaces. A gradient descent algorithm with early stopping is introduced to solve the corresponding empirical risk minimization problem associated with robust loss functions. By appropriately selecting the early stopping rule and the scaling parameter of the robust losses, the convergence of the proposed algorithm is established when the response variable is bounded or satisfies a moment condition. Explicit learning rates with respect to both estimation and prediction error are provided in terms of regularity of the regression function and eigenvalue decay rate of the integral operator induced by the reproducing kernel and covariance function.

Gain and loss cycles revisited: What to consider when testing key assumptions of conservation of resources theory

In this editorial, we discuss approaches to the empirical test of gain and loss cycles as described within Hobfoll's conservation of resources theory (COR). We present COR theory's basic assumptions about gain and loss cycles and critically discuss typical empirical studies that aim at testing these assumptions. We highlight conceptual and empirical problems when testing gain and loss cycles of resources and provide guidance for researchers with respect to theoretical, temporal, and data-analytic aspects. We offer some suggestions for constructive replications and reproducibility.

Explaining the Subjunctive in factive contexts

The occurrence of the Subjunctive mood in sentences describing facts is commonly seen as problematic, given the relation between Subjunctive and non-veridicality. One line that is explored in the literature to account for the Subjunctive in complement clauses of factive verbs is to link the occurrence of this mood in such contexts to gradability of the main clause’s predicate. However, such an account faces empirical problems, and is not extendable to other contexts where the Subjunctive occurs even if the sentence describes a fact of reality. This paper proposes an account for the occurrence of Subjunctive in different kinds of factive contexts, showing that in all such cases the reason for this mood to occur follows from the general condition that leads to the use of Subjunctive, though for different reasons. Gradability of the main predicate is, in fact, one of the factors that leads to the consideration of non-p worlds, and the Subjunctive, but not the only one. For other predicates, other semantic features lead to counterfactual reasoning. Concessive clauses are another factive context where Subjunctive occurs and allow a better understanding of what triggers the Subjunctive mood and what this formal sign indicates.

Assessment of Poland’s fiscal position in the European Union in the face of crisis conditions

Crisis conditions in the 21st century also reached the European Union countries, including Poland, and were reflected in the nominal and real economy. In particular, what suffered most was the fiscal condition of individual countries. To support the state of the economy, the economic authorities often took extraordinary, unconventional actions, which unfortunately resulted and still result in a deterioration of the state of public finances. It is therefore worth referring to this research and empirical problem from the perspective of the current and ongoing economic crisis.

ORGANIZATIONAL ATTRACTIVENESS: A THEORETICAL REVIEW OF THE MOST RELEVANT EMPIRICAL RESEARCH FROM AN INTERACTIONIST PERSPECTIVE

Purpose: This research aims to analyze and deepen the study of the Organizational Attractiveness construct, identify the main gaps in the field, and propose possible future research in this regard. Theoretical Framework: The shortage of talent in companies, the growing competition, and the new normality have made attracting talent a strategic but critical element for companies. In this sense, Organizational Attractiveness is recognized by various authors as a relevant construct to understand the attraction. In addition, these authors highlight some academic and empirical problems in this field of study. Design/Methodology/Approach: The literature review of more than 300 articles from the Scopus, Web of Science, and Google Scholar databases allowed us to analyze the content and identify 12 articles that discuss the measurement of Organizational Attractiveness under the conceptual models and theoretical framework identified. Findings: This theoretical research process has allowed us to identify four main gaps in this field of study. The gaps found are based on the comprehensive view of the dimensions of Organizational Attractiveness, the approaches to the study of Organizational Attractiveness, the methodology applied, and the sample studied. Research, Practical & Social Implications: Future research is proposed to resolve the gaps. Originality/Value: Although attraction and Organizational Attractiveness have proven strategic and critical, there is little research in the literature that acknowledges the gaps in the field of study. Identifying and closing these gaps could help companies better attract talent.

Lucas (1972) a personal view from the wrong side of the subsequent fifty years

Lucas (1972) permanently changed the course of macroeconomics, even though his “money supply surprise” model lost its central place in the area within a decade because of empirical difficulties. However, Lucas’s novel methodology, based on clearing markets and rational expectations, still dominates orthodox macroeconomic theorising. An unfortunate side effect of this has been that, because mainstream models have no analytic room for money to play a key role in economic activity, the theoretical case for taking that role seriously was undermined just at the time when traditional monetarist macro-models were facing empirical problems, not least in policy applications. Some consequences for today’s monetary policy environment are briefly discussed.

Measures of conditional dependence for nonlinearity, asymmetry and beyond

Detecting the correlation between two random variables is widely used in many empirical problems in economics. Among them, Pearson’s correlation can be used to quantify the degree of dependence between variables. However, it cannot handle asymmetric correlations. To deal with this situation, we proposed a pair of widely applicable measures of conditional dependence (MCDs), which can not only account for the asymmetry but also the linear or nonlinear conditional dependencies in the presence of multiple variables. We give instances: when the paired measures are the same, resulting in symmetric correlation measures that are equivalent to the square of the Pearson coefficient; when no condition variables are given, MCDs are used to assess the relationship between two variables. Consequently, Pearson’s correlation is a particular instance of MCDs. Theoretical attributes of MCDs show that they have wide applicability. In statistical inference, we develop the joint asymptotics of kernel-based estimators for MCDs, which can be applied to determine whether two randomly generated variables exhibit symmetric conditional dependence in the presence of confounding variables. In the simulation, we verify the efficacy of the proposed MCDs. Then we use real data to analyze the asymmetric impact of MCDs on stock market movements.

To Compress or Not to Compress-Self-Supervised Learning and Information Theory: A Review.

Deep neural networks excel in supervised learning tasks but are constrained by the need for extensive labeled data. Self-supervised learning emerges as a promising alternative, allowing models to learn without explicit labels. Information theory has shaped deep neural networks, particularly the information bottleneck principle. This principle optimizes the trade-off between compression and preserving relevant information, providing a foundation for efficient network design in supervised contexts. However, its precise role and adaptation in self-supervised learning remain unclear. In this work, we scrutinize various self-supervised learning approaches from an information-theoretic perspective, introducing a unified framework that encapsulates the self-supervised information-theoretic learning problem. This framework includes multiple encoders and decoders, suggesting that all existing work on self-supervised learning can be seen as specific instances. We aim to unify these approaches to understand their underlying principles better and address the main challenge: many works present different frameworks with differing theories that may seem contradictory. By weaving existing research into a cohesive narrative, we delve into contemporary self-supervised methodologies, spotlight potential research areas, and highlight inherent challenges. Moreover, we discuss how to estimate information-theoretic quantities and their associated empirical problems. Overall, this paper provides a comprehensive review of the intersection of information theory, self-supervised learning, and deep neural networks, aiming for a better understanding through our proposed unified approach.

Differentially private Riemannian optimization

In this paper, we study the differentially private empirical risk minimization problem where the parameter is constrained to a Riemannian manifold. We introduce a framework for performing differentially private Riemannian optimization by adding noise to the Riemannian gradient on the tangent space. The noise follows a Gaussian distribution intrinsically defined with respect to the Riemannian metric on the tangent space. We adapt the Gaussian mechanism from the Euclidean space to the tangent space compatible to such generalized Gaussian distribution. This approach presents a novel analysis as compared to directly adding noise on the manifold. We further prove privacy guarantees of the proposed differentially private Riemannian (stochastic) gradient descent using an extension of the moments accountant technique. Overall, we provide utility guarantees under geodesic (strongly) convex, general nonconvex objectives as well as under the Riemannian Polyak-Łojasiewicz condition. Empirical results illustrate the versatility and efficacy of the proposed framework in several applications.

Constructing decision rules for multiproduct newsvendors: An integrated estimation-and-optimization framework

In this paper, we develop an integrated estimation-and-optimization framework for constructing decisions rules for the order quantities of multiple perishable products. The framework accounts for substitution in case of scarcity by providing models incorporating substitution rates, received as input. Specifically, it builds decision rules minimizing the empirical risk and accommodates multiple classes of functions, including those leveraging exogenous features. We provide a continuous reformulation of the empirical risk minimization problem that is quadratic in the decision rules. In addition, we show how to incorporate information from in-sample optimal decisions to derive a linear approximation to it. The dual of this approximation allows us to estimate decision rules that exploit nonlinearities and interactions of features. The numerical results on real and simulated datasets suggest that decision rules computed within the proposed integrated framework have the potential to outperform separated estimation and optimization methods. In particular, larger improvements are obtained under low service levels requirements or high volatility of the demands. Furthermore, we empirically observe that information provided by exogenous features may be particularly significant in the presence of large fluctuations of the demand.