Philosophers of science typically focus on the epistemic performance of scientific models when evaluating them. Analysing the effects that models may have on the world has typically been the purview of sociologists of science. We argue that the reactive (or “performative”) effects of models should also figure in model evaluations by philosophers of science. We provide a detailed analysis of how models in financial economics created the impetus for the growing importance of the phenomenon of “passive investing” in financial (...) markets. Considering this case motivates the position that we call contextualism about model evaluation, or _model contextualism_ for short. Model contextualism encompasses standard analyses of the epistemic performance of the model, but also includes their reactive aspects. It entails identifying the _epistemic and contextual import of the model_, the ways in which a model can engender change in the world (which we call the _channels of transmission_), and the _interactions between the epistemic and reactive import of a model_. (shrink)

According to an adequacy-for-purpose view, models should be assessed with respect to their adequacy or fitness for particular purposes. Such a view has been advocated by scientists and philosophers...

This article reviews current methods for evaluating models in the cognitive sciences, including theoretically based approaches, such as Bayes factors and minimum description length measures; simulation approaches, including model mimicry evaluations; and practical approaches, such as validation and generalization measures. This article argues that, although often useful in specific settings, most of these approaches are limited in their ability to give a general assessment of models. This article argues that hierarchical methods, generally, and hierarchical Bayesian methods, specifically, can provide (...) a more thorough evaluation of models in the cognitive sciences. This article presents two worked examples of hierarchical Bayesian analyses to demonstrate how the approach addresses key questions of descriptive adequacy, parameter interference, prediction, and generalization in principled and coherent ways. (shrink)

Norris et al. present a sufficiency case for Merge, but not for autonomy. The simulations make clear that there is little reason to favor Merge over TRACE. The slanted presentation of the empirical evidence gives the illusion that the autonomous position is stronger than it really is.

In climate science, observational gridded climate datasets that are based on in situ measurements serve as evidence for scientific claims and they are used to both calibrate and evaluate models. However, datasets only represent selected aspects of the real world, so when they are used for a specific purpose they can be a source of uncertainty. Here, we present a framework for understanding this uncertainty of observational datasets which distinguishes three general sources of uncertainty: (1) uncertainty that arises during the (...) generation of the dataset; (2) uncertainty due to biased samples; and (3) uncertainty that arises due to the choice of abstract properties, such as resolution and metric. Based on this framework, we identify four different types of dataset ensembles — parametric, structural, resampling, and property ensembles—as tools to understand and assess uncertainties arising from the use of datasets for a specific purpose. We advocate for a more systematic generation of dataset ensembles by using these sorts of tools. Finally, we discuss the use of dataset ensembles in climate model evaluation. We argue that a more systematic understanding and assessment of dataset uncertainty is needed to allow for a more reliable uncertainty assessment in the context of model evaluation. The more systematic use of such a framework would be beneficial for both scientific reasoning and scientific policy advice based on climate datasets. (shrink)

Philosophers of science have offered various accounts of climate model evaluation which have largely centered on model-fit assessment. However, despite the wide-spread prevalence of process-based evaluation in climate science practice, this sort of model evaluation has been undertheorized by philosophers of science. In this paper, I aim to expand this narrow philosophical view of climate model evaluation by providing a philosophical account of process evaluation that is rooted in a close examination (...) of scientific practice. I propose dynamical adequacy as a metric by which scientists test and evaluate models that represent and produce key regional climate processes and features. I argue that process-based evaluation confirms the adequacy of a regional climate model for simulating and predicting future changes of a specific regional climate feature. I offer a case study of how, in practice, scientists establish the reliability of model projections by assessing the dynamical adequacy of such models. I also show how process-based evaluation mitigates some well-known shortcomings of model-fit assessment and supports the adequacy and reliability of climate model projections against philosophical objections, like confirmational holism. Such adequacy is especially important for decision makers who need reliable regional model projections to guide their climate change mitigation and adaptation policies. (shrink)

Polarization is a topic of intense interest among social scientists, but there is significant disagreement regarding the character of the phenomenon and little understanding of underlying mechanics. A first problem, we argue, is that polarization appears in the literature as not one concept but many. In the first part of the article, we distinguish nine phenomena that may be considered polarization, with suggestions of appropriate measures for each. In the second part of the article, we apply this analysis to evaluate (...) the types of polarization generated by the three major families of computational models proposing specific mechanisms of opinion polarization. (shrink)

Polarization is a topic of intense interest among social scientists, but there is significant disagreement regarding the character of the phenomenon and little understanding of underlying mechanics. A first problem, we argue, is that polarization appears in the literature as not one concept but many. In the first part of the article, we distinguish nine phenomena that may be considered polarization, with suggestions of appropriate measures for each. In the second part of the article, we apply this analysis to evaluate (...) the types of polarization generated by the three major families of computational models proposing specific mechanisms of opinion polarization. (shrink)

Though the concept of ‘stylized fact’ plays an important role in the economic literature, there is little analysis of the definition and evaluative use of the term. A permissive account of stylized facts is developed which focuses on their mediating role between models and empirical evidence. The mediation relationship restricts stylized facts by requiring concrete empirical targets. On the other hand, there is much legitimate diversity within the permissive account; key dimensions of diversity are argued to be the part of (...) the model targeted (explanans vs. explanandum) and degree of partiality of correspondence. The use of stylized fact in model evaluation points to the downside of stylization: decreased ability to support strong claims about particular targets. In the final analysis, the role of stylized facts in model-based explanation depends on the view taken of the relative importance of generality and empirical adequacy. (shrink)

This article investigates a problem for statistical model evaluation, in particular for curve fitting: by employing a different family of curves we can fit any scatter plot almost perfectly at apparently minor cost in terms of model complexity. The problem is resolved by an appeal to prior probabilities. This leads to some general lessons about how to approach model evaluation.

In natural language understanding, a crucial goal is correctly interpreting open-textured phrases. In practice, disagreements over the meanings of open-textured phrases are often resolved through the generation and evaluation of interpretive arguments, arguments designed to support or attack a specific interpretation of an expression within a document. In this paper, we discuss some of our work towards the goal of automatically generating and evaluating interpretive arguments. We have curated a set of rules from the code of ethics of various (...) professional organizations and a set of associated scenarios that are ambiguous with respect to some open-textured phrase within the rule. We collected and evaluated arguments from both human annotators and state-of-the-art generative language models in order to determine the relative quality and persuasiveness of both sets of arguments. Finally, we performed a Turing test-inspired study in order to assess whether human annotators can tell the difference between human arguments and machine-generated arguments. The results show that machine-generated arguments, when prompted a certain way, can be consistently rated as more convincing than human-generated arguments, and to the untrained eye, the machine-generated arguments can convincingly sound human-like. (shrink)

The spacing effect is among the most widely replicated empirical phenomena in the learning sciences, and its relevance to education and training is readily apparent. Yet successful applications of spacing effect research to education and training is rare. Computational modeling can provide the crucial link between a century of accumulated experimental data on the spacing effect and the emerging interest in using that research to enable adaptive instruction. In this paper, we review relevant literature and identify 10 criteria for rigorously (...) evaluating computational models of the spacing effect. Five relate to evaluating the theoretic adequacy of a model, and five relate to evaluating its application potential. We use these criteria to evaluate a novel computational model of the spacing effect called the Predictive Performance Equation. Predictive Performance Equation combines elements of earlier models of learning and memory including the General Performance Equation, Adaptive Control of Thought—Rational, and the New Theory of Disuse, giving rise to a novel computational account of the spacing effect that performs favorably across the complete sets of theoretic and applied criteria. We implemented two other previously published computational models of the spacing effect and compare them to PPE using the theoretic and applied criteria as guides. (shrink)

Storytelling is a mode of communication in human interaction and is pervasive in everyday life. Storytelling in marketing is also a managerial application as a marketing strategy. Researchers of consumer psychology and marketing have devoted great efforts to developing theories and conducting empirical studies on this approach. However, in addition to narrative theories, many researchers are mainly concerned about the effect of telling a good brand story and its applications, such as advertising design and presentation. However, for those products that (...) usually lack branding, such as agricultural products, knowledge remains scarce about the relative impact of storytelling in marketing. Few researchers have explicitly developed a valid tool for measuring the effect of storytelling in marketing. To aid storytelling research in consumer psychology, this article conceptualized a construct of the effectiveness of storytelling in agricultural marketing and developed a measure with further validation. This scale consisted of 13 items with four subscales: narrative processing, affect, brand attitude, and purchase intention. The findings of this study strongly supported a structural model with strong order among the four dimensions and good model fit. A discussion of the results and the theoretical and practical implications for consumer psychology and marketing practice are also addressed. (shrink)

In the target article, Bowers et al. dispute deep artificial neural network (ANN) models as the currently leading models of human vision without producing alternatives. They eschew the use of public benchmarking platforms to compare vision models with the brain and behavior, and they advocate for a fragmented, phenomenon-specific modeling approach. These are unconstructive to scientific progress. We outline how the Brain-Score community is moving forward to add new model-to-human comparisons to its community-transparent suite of benchmarks.

Artificial models of cognition serve different purposes, and their use determines the way they should be evaluated. There are also models that do not represent any particular biological agents, and there is controversy as to how they should be assessed. At the same time, modelers do evaluate such models as better or worse. There is also a widespread tendency to call for publicly available standards of replicability and benchmarking for such models. In this paper, I argue that proper evaluation (...) ofmodels does not depend on whether they target real biological agents or not; instead, the standards of evaluation depend on the use of models rather than on the reality of their targets. I discuss how models are validated depending on their use and argue that all-encompassing benchmarks for models may be well beyond reach. (shrink)

In spite of the wide variety of approaches to ethics training it is still debatable which approach has the highest potential to enhance professionals’ integrity. The current effort assesses a novel curriculum that focuses on metacognitive reasoning strategies researchers use when making sense of day-to-day professional practices that have ethical implications. The evaluated trainings effectiveness was assessed by examining five key sensemaking processes, such as framing, emotion regulation, forecasting, self-reflection, and information integration that experts and novices apply in ethical decision-making. (...) Mental models of trained and untrained graduate students, as well as faculty, working in the field of physical sciences were compared using a think-aloud protocol 6 months following the ethics training. Evaluation and comparison of the mental models of participants provided further validation evidence for sensemaking training. Specifically, it was found that trained students applied metacognitive reasoning strategies learned during training in their ethical decision-making that resulted in complex mental models focused on the objective assessment of the situation. Mental models of faculty and untrained students were externally-driven with a heavy focus on autobiographical processes. The study shows that sensemaking training has a potential to induce shifts in researchers’ mental models by making them more cognitively complex via the use of metacognitive reasoning strategies. Furthermore, field experts may benefit from sensemaking training to improve their ethical decision-making framework in highly complex, novel, and ambiguous situations. (shrink)

This study focuses on implementing electric vehicles (EVs) in developing countries where energy production is mainly based on fossil fuels. Although for these countries the environmental short-run benefits of the EVs cannot offset the short-run costs, it may still be the best option to implement the EVs as soon as possible. Hence, it is necessary to evaluate the alternatives to introducing EVs to the market due to the environmental concerns that created an opportunity for some developing countries to catch up (...) with the international competition. Therefore, we develop a case scenario to explore the decision-making process in implementing the EVs with three alter natives and twelve criteria. We solve the decision-making problem by using Type-2 neutrosophic numbers (T2NNs) based on the RAFSI (Ranking of Alternatives through Functional mapping of criterion sub-intervals into a Single Interval) method. The proposed model combines the advantages of the RAFSI technique, and it applies T2NNs to address the uncertainties. The results show that the alternatives that may suspend the implementation of the EVs are inferior. Direct implementation of EVs is prioritized. The policy implications of the results are discussed in the study. (shrink)

Cloud computing (ClC) has become a more popular computer paradigm in the preceding few years. Quality of Service (QoS) is becoming a crucial issue in service alteration because of the rapid growth in the number of cloud services. When evaluating cloud service functioning using several performance measures, the issue becomes more complex and non-trivial. It is therefore quite difficult and crucial for consumers to choose the best cloud service. The user's choices are provided in a quantifiable manner in the current (...) methods for choosing cloud services. Hence, this study attempts to achieve this objective through construction. decision-making framework so-called cloud services evaluator (CSsEv). The main indicator and its sub-indicators are formed as nodes at levels(n) in tree soft sets (TSSs). Thereafter Single Value Neutrosophic Sets (SVNSs) as branch of neutrosophic sets which conjunction with the Multi-Criteria Decision Making (MCDM) technique to facilitate analysis and evaluation process for the available Cloud services providers. Hence, entropy is employed to obtain indicators and sub_indicators weights and Complex Proportional Assessment utilizes these weights to facilitate the decision process of selecting optimal ClSPs. (shrink)

Building on prior research related to impact of information communication technology and operational risk management in the context of medium and small enterprises, the focus of this study was to investigate the relationship between ICT operational risk management and performances of MSEs. To achieve the focus, the research investigated evaluating models for understanding the value of ICT ORM in MSEs. Multiple regression, Repeated-Measures Analysis of Variance and Repeated-Measures Multivariate Analysis of Variance were performed. The findings of the distribution revealed that (...) only one variable made a significant percentage contribution to the level of ICT operation in MSEs, the Payback method. It may thus be inferred that the Payback method is the prominent variable, explaining the variation in level of evaluation models affecting ICT adoption within MSEs. Conclusively, in answering the two questions degree of variability explained and predictors, the results revealed that the variable contributed approximately 88.4% of the variations in evaluation models affecting ICT adoption within MSEs. The analysis of variance also revealed that the regression coefficients were real and did not occur by chance. (shrink)

Normal.dotm 0 0 1 66 378 Thorbjoern Mann Consulting 3 1 464 12.256 0 false 18 pt 18 pt 0 0 false false false Normal.dotm 0 0 1 80 459 Thorbjoern Mann Consulting 3 1 563 12.256 0 false 18 pt 18 pt 0 0 false false false Arguments commonly used in discussions about design, planning, policy-making issues have not been adequately analyzed in the literature. The structure of such ‘planning arguments’ is discussed. Based on the conceptual framework of the (...) ‘argumentative model of planning’ proposed by H. Rittel, an approach for their systematic and transparent evaluation by discourse participants is presented. Procedural implications for its application in the planning process are discussed, and the potential for information technology support for such processes explored. (shrink)

Computational modelling has proven to be a valuable approach in developing theories of spoken-word processing. In this paper, we focus on a particular class of theories in which it is assumed that the spoken-word recognition process consists of two consecutive stages, with an `abstract' discrete symbolic representation at the interface between the stages. In evaluating computational models, it is important to bring in independent arguments for the cognitive plausibility of the algorithms that are selected to compute the processes in a (...) theory. This paper discusses the relation between behavioural studies, theories, and computational models of spoken-word recognition. We explain how computational models can be assessed in terms of the goodness of fit with the behavioural data and the cognitive plausibility of the algorithms. An in-depth analysis of several models provides insights into how computational modelling has led to improved theories and to a better understanding of the human spoken-word recognition process. (shrink)

Extended redundancy analysis is a statistical method that relates multiple sets of predictors to response variables. In ERA, the conventional approach of model evaluation tends to overestimate the performance of a model since the performance is assessed using the same sample used for model development. To avoid the overly optimistic assessment, we introduce a new model evaluation approach for ERA, which utilizes computer-intensive resampling methods to assess how well a model performs on unseen (...) data. Specifically, we suggest several new model evaluation metrics for ERA that compute a model’s performance on out-of-sample data, i.e., data not used for model development. Although considerable work has been done in machine learning and statistics to examine the utility of cross-validation and bootstrap variants for assessing such out-of-sample predictive performance, to date, no research has been carried out in the context of ERA. We use simulated and real data examples to compare the proposed model evaluation approach with the conventional one. Results show the conventional approach always favor more complex ERA models, thereby failing to prevent the problem of overfitting in model selection. Conversely, the proposed approach can select the true ERA model among many mis-specified models. (shrink)

Solvency assessment is the core content of insurance supervision. In this paper, from the perspective of capital flow, the insurance company’s capital flow is regarded as a dynamic system, the stochastic differential equations model is established to describe its flow characteristics, and the existence of positive equilibrium point of the system is proved, as well as the conditions of stability at equilibrium point, that is, the requirements of the insurance company’s solvency. Furthermore, by using the numerical simulation method, we (...) get the strategy of insurance companies to deal with the solvency shortage when facing the change of external environment, and the strategy of insurance company to deal with solvency shortage is obtained. (shrink)

The seminal 1993 article by LaFollette and Shanks “Animal Models in Biomedical Research: Some Epistemological Worries” introduced an influential taxonomy into the debate about the value of animal experimentation. The distinction they made between hypothetical and causal analog models served to highlight a concern regarding extrapolating results obtained in animal models to human subjects, which endures today. Although their taxonomy has made a significant contribution to the field, we maintain that it is flawed, and instead, we offer a new practice-oriented (...) taxonomy of animal models as a means to allow philosophers, modelers, and other interested parties to discuss the epistemic merits and shortcomings, purpose, and predictive capacities of specific modeling practices. (shrink)

Mental models influence how individuals think and act in relation to their external environment and have been identified as leverage points to address sustainability challenges. Given the importance of mental models, a new tool to assess mental models has been developed: the Mental Model Mapping Tool. M-Tool was designed to have a standardized format and to be user-friendly for low literacy populations, using pictograms and audio instructions. In this paper, we evaluate M-Tool’s application in two studies with Tanzanian fishers. (...) In Study 1, we investigated M-tool’s convergent validity compared to standard interviewing methods. Study 2 investigated M-Tool’s construct validity by relating mental model complexity to participants’ education level, a relationship that has been well established. The findings show that mental models produced with M-Tool are more complex than mental models obtained through interviewing techniques; model composition is similar across the two methods; and participants with higher levels of education tend to produce more complex mental models with M-Tool than participants with lower levels of education, in line with previous research. These findings suggest that M-Tool can successfully capture mental models among diverse participants. This tool offers researchers and practitioners an instrument to map and compare perceptions of challenges across groups. (shrink)

This paper presents an account of how to evaluate formal models of science: models and simulations in social epistemology designed to draw normative conclusions about the social structure of scientific research. I argue that such models should be evaluated according to their representational and predictive accuracy. Using these criteria and comparisons with familiar models from science, I argue that most formal models of science are incapable of supporting normative conclusions.

While Specific Informed Consent has been the established standard for obtaining consent for medical research for many years, it does not appear suitable for large-scale biobank and health data research. Thus, alternative forms of consent have been suggested, based on a variety of ethical background assumptions. This article identifies five main ethical perspectives at stake. Even though Tiered Consent, Dynamic Consent and Meta Consent are designed to the demands of the self-determination perspective as well as the perspective of research as (...) a public good, they are still also criticized from both perspectives. In addition, criticisms based on concerns of justice, participation and democratic deliberation, and relational concerns have been levelled at each of the models. As all of these perspectives have valid points to make, the task at hand lies in balancing these ethical perspectives. What constitutes an adequate balancing depends on contextual factors. These factors include digital infrastructure and digital literacy, data safety regulation, good scientific and clinical practice, transparent debates on ethically relevant features of research, social inequalities, anti-discrimination laws and practices, trust in health care institutions and recognition of patient preferences, and consensus on unethical research. We argue that the role of context in determining acceptable models of consent puts the ethical importance of models of consent into perspective. Since altering contextual factors can help to live up to the ethical concerns at stake in debates about models of consent, opting for such a shift of focus comes without ethical loss. (shrink)

Lisciandra poses a challenge for robustness analysis as applied to economic models. She argues that substituting tractability assumptions risks altering the main mathematical structure of the model, thereby preventing the possibility of meaningfully evaluating the same model under different assumptions. In such cases RA is argued to be inapplicable. However, Lisciandra is mistaken to take the goal of RA as keeping the mathematical properties of tractability assumptions intact. Instead, RA really aims to keep the modeling component while varying (...) the corresponding mathematical formulation. Thus, her argument concerning whether the associated mathematical properties of certain assumptions can be kept intact is irrelevant to the success of RA. Furthermore, we explicate and develop Lloyd’s account of “model robustness” to provide solutions to Lisciandra’s challenges. Our solutions are, namely, error analysis and independent empirical support. We conclude that although complex economic models do face potential dangers, there are solutions and robustness analysis need not be given up.. (shrink)

This paper provides a historical analysis of a shift in the way animal models of mental disorders were conceptualized: the shift from the mid-twentieth-century view, adopted by some, that animal models model syndromes classified in manuals such as the Diagnostic and Statistical Manual of Mental Disorders (DSM), to the later widespread view that animal models model component parts of psychiatric syndromes. I argue that in the middle of the twentieth century the attempt to maximize the face validity of (...) animal models sometimes led to the pursuit of the ideal of an animal model that represented a behaviorally defined psychiatric syndrome as described in manuals such as the DSM. I show how developments within psychiatric genetics and related criticism of the DSM in the 1990s and 2000s led to the rejection of this ideal and how researchers in the first decade of the twenty-first century came to believe that animal models of mental disorders should model component parts of mental disorders, adopting a so-called endophenotype approach. (shrink)

In this article we raise a problem, and we offer two practical contributions to its solution. The problem is that academic communities interested in digital publishing do not have adequate tools to help them in choosing a publishing model that suits their needs. We believe that excessive focus on Open Access (OA) has obscured some important issues; moreover exclusive emphasis on increasing openness has contributed to an agenda and to policies that show clear practical shortcomings. We believe that academic (...) communities have different needs and priorities; therefore there cannot be a ranking of publishing models that fits all and is based on only one criterion or value. We thus believe that two things are needed. First, communities need help in working out what they want from their digital publications. Their needs and desiderata should be made explicit and their relative importance estimated. This exercise leads to the formulation and ordering of their objectives. Second, available publishing models should be assessed on the basis of these objectives, so as to choose one that satisfies them well. Accordingly we have developed a framework that assists communities in going through these two steps. The framework can be used informally, as a guide to the collection and systematic organization of the information needed to make an informed choice of publishing model. In order to do so it maps the values that should be weighed and the technical features that embed them. Building on our framework, we also offer a method to produce ordinal and cardinal scores of publishing models. When these techniques are applied the framework becomes a formal decision–making tool. Finally, the framework stresses that, while the OA movement tackles important issues in digital publishing, it cannot incorporate the whole range of values and interests that are at the core of academic publishing. Therefore the framework suggests a broader agenda that is relevant in making better policy decisions around academic publishing and OA. (shrink)

This paper addresses the field of economic measurements of the value of assets, carried out by the methods of independent expert evaluation. The mathematical principles of application, within a comparative methodical approach, of additive and multiplicative models for correcting the cost of single indicator of compared objects have been considered. The differences of mathematical basis of the compared models were analyzed. It has been shown that the ambiguity in the methodology of correction procedure requires studying the advantages and disadvantages (...) of known models, as well as the justification and elaboration of recommendations for their application. Possible forms of correction representation using several alternative units of measurement have been defined; formulas for their interconnection have been built. Analytic expressions have been derived that mathematically describe the algorithms for performing the evaluation correction procedure using various forms of correction representation. The influence of the correction execution model on the characteristics of uncertainty in the independent evaluation result has been analyzed. The scope of two possible types of correction introduction models has been determined. A specific numerical example was used to demonstrate the methodological advantages of using a multiplicative model when summarizing percentage corrections. The independence of the correction result on the sequence of correction introduction has been confirmed. It is proposed to use the selected measure of partial corrections as a criterion for the adequacy of the correction introduction model. It is proved that the result of the independent expert evaluation depends on the chosen model and does not depend on the sequence of correction introduction. The reported study results are important in terms of theory and practice since they make it possible to improve the accuracy and reliability of the result of independent expert evaluation. (shrink)

As a part of user experience, user emotion has rarely been studied in mobile libraries. Specifically, with the proposed emotional model in combination with the Pleasure-Arousal-Dominance Emotion Model and the Five Factor Model, we evaluate user emotions on the mobile library’s three IS features. An experience procedure with three tasks has been designed to collect data. 50 participants were enrolled, and they were asked to fill in questionnaires right after the experience. The correlations among the PAD emotions (...) were examined. Specifically, users have a low perception of pleasure, high perception of arousal, and low perception of dominance. However, these three emotional states were not always significantly correlated with each other. This study extends mobile library research by focusing on users’ emotional experience. Specifically, the detailed PAD emotions have been examined. This study provides a new approach for application developers and managers to evaluate the user experience of an application. (shrink)

Many important decisions depend on unknown states of the world. Society is increasingly relying on statistical predictive models to make decisions in these cases. While predictive models are useful, previous research has documented that (a) individual decision makers distrust models and (b) people’s predictions are often worse than those of models. These findings indicate a lack of awareness of how to evaluate predictions generally. This includes concepts like the loss function used to aggregate errors or whether error is training error (...) or generalisation error. To address this gap, we present three studies testing how lay people visually evaluate the predictive accuracy of models. We found that (a) participant judgements of prediction errors were more similar to absolute error than squared error (Study 1), (b) we did not detect a difference in participant reactions to training error versus generalisation error (Study 2), and (c) participants rated complex models as more accurate when comparing two models, but rated simple models as more accurate when shown single models in isolation (Study 3). When communicating about models, researchers should be aware that the public’s visual evaluation of models may disagree with their method of measuring errors and that many may fail to recognise overfitting. (shrink)

Should journalists resist business constraints they perceive as a threat to their professional integrity? This article suggests that the answer, at least sometimes, is yes. But in choosing a resistance strategy, journalists should not consider the "take this job and shove it" stance as the only option with moral integrity-or even as the best ethical option. This article develops a model of resistance strategies using the experiences of journalists at one newspaper to illustrate the range of options available for (...) resisting business constraints within a news organization. The types of strategies identified vary along the ethical dimensions of consideration of organizational, as well as professional, goals; and openness with regard to journalists' preference for professional goals. (shrink)

Spoken communication occurs in a “noisy channel” characterized by high levels of environmental noise, variability within and between speakers, and lexical and syntactic ambiguity. Given these properties of the received linguistic input, robust spoken word recognition—and language processing more generally—relies heavily on listeners' prior knowledge to evaluate whether candidate interpretations of that input are more or less likely. Here we compare several broad-coverage probabilistic generative language models in their ability to capture human linguistic expectations. Serial reproduction, an experimental paradigm where (...) spoken utterances are reproduced by successive participants similar to the children's game of “Telephone,” is used to elicit a sample that reflects the linguistic expectations of English-speaking adults. When we evaluate a suite of probabilistic generative language models against the yielded chains of utterances, we find that those models that make use of abstract representations of preceding linguistic context (i.e., phrase structure) best predict the changes made by people in the course of serial reproduction. A logistic regression model predicting which words in an utterance are most likely to be lost or changed in the course of spoken transmission corroborates this result. We interpret these findings in light of research highlighting the interaction of memory-based constraints and representations in language processing. (shrink)

A method for the recursive identification of physiological models of the cardiovascular baroreflex is proposed and applied to the time-varying analysis of vagal and sympathetic activities. The proposed method was evaluated with data from five newborn lambs, which were acquired during injection of vasodilator and vasoconstrictors and the results show a close match between experimental and simulated signals. The model-based estimation of vagal and sympathetic contributions were consistent with physiological knowledge and the obtained estimators of vagal and sympathetic activities (...) were compared to traditional markers associated with baroreflex sensitivity. High correlations were observed between traditional markers and model-based indices. (shrink)

Human affectivity is a research topic situated at the intersection of psychology, philosophical anthropology, theory of action and ethics. This article reconstructs the Aristotelian theory of emotions in the context of his theory of aspiration /recij ) and in terms of their function as primary evaluators of situations, which forms the basis for virtue ethics. The Aristotelian model integrates desire, motivation and morality for a rational being in community. Affects reveal the profile of relevance of the world to a (...) person as an indispensable basis for the work of practical reason. They are analysed in the dimensions of their cognitive core, their social, bodily, and motivational aspects. Affectivity constitutes a primary evaluative response to situations and thereby disposes human beings to realise their call to morally good, virtuous and fulfilling action. (shrink)

This article reviews research on counterfactual, social, and temporal comparisons and proposes a Reflection and Evaluation Model (REM) as an organizing framework. At the heart of the model is the assertion that 2 psychologically distinct modes of mental simulation operate during comparative thinking: reflection, an experiential (“as if”) mode of thinking characterized by vividly simulating that information about the comparison standard is true of, or part of, the self; and evaluation, an evaluative mode of thinking characterized (...) by the use of information about the standard as a reference point against which to evaluate one’s present standing. Reflection occurs when information about the standard is included in one’s self-construal, and evaluation occurs when such information is excluded. The result of reflection is that standard–consistent cognitions about the self become highly accessible, thereby yielding affective assimilation; whereas the result of evaluation is that comparison information is used as a standard against which one’s present standing is evaluated, thereby yielding affective contrast. The resulting affect leads to either an increase or decrease in behavioral persistence as a function of the type of task with which one is engaged, and a combination of comparison-derived causal inferences and regulatory focus strategies direct one toward adopting specific future action plans. (shrink)

People with aphasia use gestures not only to communicate relevant content but also to compensate for their verbal limitations. The Sketch Model (De Ruiter, 2000) assumes a flexible relationship between gesture and speech with the possibility of a compensatory use of the two modalities. In the successor of the Sketch Model, the AR‐Sketch Model (De Ruiter, 2017), the relationship between iconic gestures and speech is no longer assumed to be flexible and compensatory, but instead iconic gestures are (...) assumed to express information that is redundant to speech. In this study, we evaluated the contradictory predictions of the Sketch Model and the AR‐Sketch Model using data collected from people with aphasia as well as a group of people without language impairment. We only found compensatory use of gesture in the people with aphasia, whereas the people without language impairments made very little compensatory use of gestures. Hence, the people with aphasia gestured according to the prediction of the Sketch Model, whereas the people without language impairment did not. We conclude that aphasia fundamentally changes the relationship of gesture and speech. (shrink)

A central theme in western philosophy was to find formal methods that can reliably discover empirical relationships and their explanations from data assembled from experience. As a philosophical project, that ambition was abandoned in the 20th century and generally dismissed as impossible. It was replaced in philosophy by neo-Kantian efforts at reconstruction and justification, and in professional statistics by the more limited ambition to estimate a small number of parameters in pre-specified hypotheses. The influx of “big data” from climate science, (...) neuropsychology, biology, astronomy and elsewhere implicitly called for a revival of the grander philosophical ambition. Search algorithms are meeting that call, but they pose a problem: how are their accuracies to be assessed in domains where experimentation is limited or impossible? Increasingly, the answer is through simulation of data from models of the kind of process in the domain. In some cases, these innovations require rethinking how the accuracy and informativeness of inference methods can be assessed. Focusing on causal inference, we give an example from neuroscience, but to show that the model/simulation strategy is not confined to causal inference, we also consider two classification problems from astrophysics: identifying exoplanets and identifying dark matter concentrations. (shrink)

People with aphasia use gestures not only to communicate relevant content but also to compensate for their verbal limitations. The Sketch Model (De Ruiter, 2000) assumes a flexible relationship between gesture and speech with the possibility of a compensatory use of the two modalities. In the successor of the Sketch Model, the AR‐Sketch Model (De Ruiter, 2017), the relationship between iconic gestures and speech is no longer assumed to be flexible and compensatory, but instead iconic gestures are (...) assumed to express information that is redundant to speech. In this study, we evaluated the contradictory predictions of the Sketch Model and the AR‐Sketch Model using data collected from people with aphasia as well as a group of people without language impairment. We only found compensatory use of gesture in the people with aphasia, whereas the people without language impairments made very little compensatory use of gestures. Hence, the people with aphasia gestured according to the prediction of the Sketch Model, whereas the people without language impairment did not. We conclude that aphasia fundamentally changes the relationship of gesture and speech. (shrink)

The city of Kruja (Albania)contains three types of dwellings that date back to different periods of time: the historic ones, the socialist ones, the modern ones. This paper has to deal only with the historic building's typology. The questionnaire that is applied will be considered for the development of mathematical regression based on specific data for this category. Variation between the relevant variables of the questionnaire is fairly or inverse-linked with a certain percentage of influence. The aim of this study (...) is to have better insights into the important role of building occupancy, people's lifestyle, economic level, and the quality of life of the residents in the inner medieval citadel, the physics characteristics, and the energy efficiency of the historical dwellings. The variables such as the number of residents, quality of life, the surface of the dwellings, heating instruments and time spent in the dwelling, current living conditions, monthly bills, level of satisfaction, restoration, and building improvements, interact with each other with probabilities with different positive or negative percentages. (shrink)