The Representational Theory of Measurement conceives measurement as establishing homomorphisms from empirical relational structures into numerical relation structures, called models. There are two different approaches to deal with the justification of a model: an axiomatic and an empirical approach. The axiomatic approach verifies whether a given relational structure satisfies certain axioms to secure homomorphic mapping. The empirical approach conceives models to function as measuring instruments by transferring observations of a phenomenon under investigation into quantitative facts about that phenomenon. These facts (...) are evaluated by their accuracy and precision. Precision is generally achieved by least squares methods and accuracy by calibration. For calibration standards are needed. Then two polar strategies can be distinguished: white-box modeling and black-box modeling. The first strategy of modeling aims at estimating the invariant equations of the phenomenon, thereby fulfilling Hertz’s correctness requirement. The latter strategy of modeling is to use known stable facts about the phenomenon to adjust the model parameters, thereby fulfilling Hertz’s appropriateness requirement. For this latter strategy, the requirement of models as homomorphic mappings has been dropped. Where one will find the axiomatic approach more often used for measurement in the laboratory, the empirical approach is more appropriate for measurement outside the laboratory. The reason for this is that for measurement of phenomena outside the laboratory, one also needs to take account of the environment to achieve accurate results. Environments are generally too relation-rich for an axiomatic approach, which are only applicable for relation-poor systems. The white-box modeling strategy, reflecting the complexity of the environment due to its correctness requirement, will, however, lead to immensely large models. To avoid this problem, modular design is an appropriate strategy to reduce this complexity. Modular design is a grey-box modeling strategy. Grey-box models are assemblies of modules; these are black boxes with standard interface. It should be noted that the structure of the assemblage need not be homomorphic to the relations describing the interaction between phenomenon and environment. These three modeling strategies map out the possible designs for computer simulations as measuring instruments. Whether a simulation is based on a white-box, grey-box or black-box model is only determined by the relationship between the phenomenon and its environment and not by e.g. its materiality or physicality. (shrink)

John Maynard Smith is the person most responsible for the use of game theory in evolutionary biology, having introduced and developed its major concepts, and later surveyed its uses. In this paper I look at some rhetorical work done by Maynard Smith and his co-author G.R. Price to make game theory a standard and common modelling tool for the evolutionary study of behavior. The original presentation of the ideas — in a 1973 Nature article — is frequently cited but (...) almost certainly rarely read. It took reformulation of the approach to create a usable model and an object of study. Perhaps paradoxically, the new model dealt with more abstract objects than did its predecessor, but because of that a better case could be made for its realism. The particular strategy of abstraction allowed game-theoretic modelling to gain a certain measure of autonomy from empirical problems, and thus to flourish. (shrink)

Green offers us two options: either connectionist models are literal models of brain activity or they are mere instruments, with little or no ontological significance. According to Green, only the first option renders connectionist models genuinely explanatory. I think there is a third possibility. Connectionist models are not literal models of brain activity, but neither are they mere instruments. They are abstract, IDEALISED models of the brain that are capable of providing genuine explanations of cognitive phenomena.

Rather than taking the ontological fundamentality of an ideal microphysics as a starting point, this article sketches an approach to the problem of levels that swaps assumptions about ontology for assumptions about inquiry. These assumptions can be implemented formally via computational modeling techniques that will be described below. It is argued that these models offer a way to save some of our prominent commonsense intuitions concerning levels. This strategy offers a way of exploring the individuation of higher level properties in (...) a systematic and formally constrained manner. †To contact the author, please write to: Department of Philosophy, Worrell Hall 306, 500 University Avenue, University of Texas, El Paso, TX 79968; e‐mail: [email protected]. (shrink)

The continued development of General Circulation Models (GCMs) towards increasing resolution and complexity is a predominantly chosen strategy to advance climate science, resulting in channelling of research and funding to meet this aspiration. Yet many other modelling strategies have also been developed and can be used to understand past and present climates, to project future climates and ultimately to support decision-making. We argue that a plurality of climate modelling strategies and an equitable distribution of funding among (...) them would be an improvement on the current predominant strategy for informing policy making. To support our claim, we use a philosophy of science approach to compare increasing resolution and complexity of General Circulation Models with three alternate examples: the use of machine learning techniques, the physical climate storyline approach, and Earth System Models of Intermediate Complexity. We show that each of these strategies prioritises a particular set of methodological aims, among which are empirical agreement, realism, comprehensiveness, diversity of process representations, inclusion of the human dimension, reduction of computational expense, and intelligibility. Thus, each strategy may provide adequate information to support different specific kinds of research and decision questions. We conclude that, because climate decision-making consists of different kinds of questions, many modelling strategies are all potentially useful, and can be used in a complementary way. (shrink)

Experimental modeling in biology involves the use of living organisms (not necessarily so-called "model organisms") in order to model or simulate biological processes. I argue here that experimental modeling is a bona fide form of scientific modeling that plays an epistemic role that is distinct from that of ordinary biological experiments. What distinguishes them from ordinary experiments is that they use what I call "in vivo representations" where one kind of causal process is used to stand in for a physically (...) different kind of process. I discuss the advantages of this approach in the context of evolutionary biology. (shrink)

In 1966, Richard Levins argued that there are different strategies in model building in population biology. In this paper, I reply to Orzack and Sober’s (1993) critiques of Levins, and argue that his views on modeling strategies apply also in the context of evolutionary genetics. In particular, I argue that there are different ways in which models are used to ask and answer questions about the dynamics of evolutionary change, prospectively and retrospectively, in classical versus molecular evolutionary genetics. (...) Further, I argue that robustness analysis is a tool for, if not confirmation, then something near enough, in this discipline. (shrink)

Both von Neumann and Wiener were outsiders to biology. Both were inspired by biology and both proposed models and generalizations that proved inspirational for biologists. Around the same time in the 1940s von Neumann developed the notion of self reproducing automata and Wiener suggested an explication of teleology using the notion of negative feedback. These efforts were similar in spirit. Both von Neumann and Wiener used mathematical ideas to attack foundational issues in biology, and the concepts they articulated had lasting (...) effect. But there were significant differences as well. Von Neumann presented a how-possibly model, which sparked interest by mathematicians and computer scientists, while Wiener collaborated more directly with biologists, and his proposal influenced the philosophy of biology. The two cases illustrate different strategies by which mathematicians, the “professional outsiders” of science, can choose to guide their engagement with biological questions and with the biological community, and illustrate different kinds of generalizations that mathematization can contribute to biology. The different strategies employed by von Neumann and Wiener and the types of models they constructed may have affected the fate of von Neumann’s and Wiener’s ideas – as well as the reputation, in biology, of von Neumann and Wiener themselves. (shrink)

In this chapter we discuss a modal logic of substitutions which provide us a way to describe winning strategies in hide and seek game played over any game graph. To this end, a modal logic of iterated substitutions is proposed, and a number of properties of this logic are explored including their expressive strength and satisfiability problems. The proposed framework is also compared with the existing ones involving iterative reasoning, which in turn showcases certain advantages of the proposal.

In the 1960s, theoretical biologist Richard Levins criticised modellers in his own discipline of population biology for pursuing the “brute force” strategy of building hyper-realistic models. Instead of exclusively chasing complexity, Levins advocated for the use of multiple different kinds of complementary models, including much simpler ones. In this paper, I argue that the epistemic challenges Levins attributed to the brute force strategy still apply to state-of-the-art climate models today: they have big appetites for unattainable data, they are limited by (...) computational tractability, and they are incomprehensible to the human modeller. Along the lines Levins described, this uncertainty generates a trade-off between realistic, precise models with predictive power and simple, highly idealised models that facilitate understanding. In addition to building ensembles of highly complex dynamical models, climate modellers can address model uncertainty by comparing models of different types, such as dynamical and data-driven models, and by systematically comparing models at different levels of what climate modellers call the model hierarchy. Despite its age, Levins’ paper remains incredibly insightful and should be considered an important entry into the philosophy of computational modelling. (shrink)

Mesoscale modeling is often considered merely as a practical strategy used when information on lower-scale details is lacking, or when there is a need to make models cognitively or computationally tractable. Without dismissing the importance of practical constraints for modeling choices, we argue that mesoscale models should not just be considered as abbreviations or placeholders for more “complete” models. Because many systems exhibit different behaviors at various spatial and temporal scales, bottom-up approaches are almost always doomed to fail. Mesoscale models (...) capture aspects of multi-scale systems that cannot be parameterized by simple averaging of lower-scale details. To understand the behavior of multi-scale systems, it is essential to identify mesoscale parameters that “code for” lower-scale details in a way that relate phenomena intermediate between microscopic and macroscopic features. We illustrate this point using examples of modeling of multi-scale systems in materials science and biology, where identification of material parameters such as stiffness or strain is a central step. The examples illustrate important aspects of a so-called “middle-out” modeling strategy. Rather than attempting to model the system bottom-up, one starts at intermediate scales where systems exhibit behaviors distinct from those at the atomic and continuum scales. One then seeks to upscale and downscale to gain a more complete understanding of the multi-scale system. The cases highlight how parameterization of lower-scale details not only enables tractable modeling but is also central to understanding functional and organizational features of multi-scale systems. (shrink)

In this essay, I argue for four related claims. First, Richard Levins’ classic “The Strategy of Model Building in Population Biology” was a statement and defense of theoretical population biology growing out of collaborations between Robert MacArthur, Richard Lewontin, E. O. Wilson, and others. Second, I argue that the essay served as a response to the rise of systems ecology especially as pioneered by Kenneth Watt. Third, the arguments offered by Levins against systems ecology and in favor of his own (...) methodological program are best construed as “pragmatic”. Fourth, I consider limitations of Levins’ arguments given contemporary population biology. (shrink)

“The Strategy of Model Building in Population Biology” published by Richard Levins in 1966 has been cited over 2500 times. For a paper concerned with modeling approaches in population biology a surprisingly large part of the attention. The Strategy received comes from history and philosophy of biology, and specifically from accounts on model and model formulation. The Strategy is an unusual paper; it presents neither new data nor a new formal model; at times it reads like a manifesto for some (...) modeling approach, without specifying which broader program that approach intends to support. When these peculiarities of The Strategy are even mentioned, the philosophical literature tends to explain them away by invoking Levins’ Marxist commitments. In contrast, I argue that those peculiarities can be explained by examining the programmatic purpose of the paper; starting from his doctoral work, Levins was trying to establish a research program meant to account for the relations between fitness and environment in different terms than the prevalent lock-and-key view. My paper brings that program back to the discussion, explains its relation to competing approaches and examines Levins’ approach to modeling in light of that context. (shrink)

Some accounts of evidence regard it as an objective relationship holding between data and hypotheses, perhaps mediated by a testing procedure. Mayo’s error-statistical theory of evidence is an example of such an approach. Such a view leaves open the question of when an epistemic agent is justified in drawing an inference from such data to a hypothesis. Using Mayo’s account as an illustration, I propose a framework for addressing the justification question via a relativized notion, which I designate security , (...) meant to conceptualize practices aimed at the justification of inferences from evidence. I then show how the notion of security can be put to use by showing how two quite different theoretical approaches to model criticism in statistics can both be viewed as strategies for securing claims about statistical evidence. (shrink)

Humans use their spatial information processing abilities flexibly to facilitate problem solving and decision making in a variety of tasks. This article explores the question of whether a general strategy can be adapted for performing two different spatial orientation tasks by testing the predictions of a computational cognitive model. Human performance was measured on an orientation task requiring participants to identify the location of a target either on a map (find‐on‐map) or within an egocentric view of a space (find‐in‐scene). A (...) general strategy instantiated in a computational cognitive model of the find‐on‐map task, based on the results from, was adapted to perform both tasks and used to generate performance predictions for a new study. The qualitative fit of the model to the human data supports the view that participants were able to tailor a general strategy to the requirements of particular spatial tasks. The quantitative differences between the predictions of the model and the performance of human participants in the new experiment expose individual differences in sample populations. The model provides a means of accounting for those differences and a framework for understanding how human spatial abilities are applied to naturalistic spatial tasks that involve reasoning with maps. (shrink)

Molecular biologists exploit information conveyed by mechanistic models for experimental purposes. In this article, I make sense of this aspect of biological practice by developing Keller’s idea of the distinction between ‘models of’ and ‘models for’. ‘Models of (phenomena)’ should be understood as models representing phenomena and are valuable if they explain phenomena. ‘Models for (manipulating phenomena)’ are new types of material manipulations and are important not because of their explanatory force, but because of the interventionist strategies they afford. (...) This is a distinction between aspects of the same model. In molecular biology, models may be treated either as ‘models of’ or as ‘models for’. By analysing the discovery and characterization of restriction–modification systems and their exploitation for DNA cloning and mapping, I identify the differences between treating a model as a ‘model of’ or as a ‘model for’. These lie in the cognitive disposition of the modeller towards the model: a modeller will look at a model as a ‘model of’ if interested in its explanatory force, or as a ‘model for’ if interested in the material manipulations it can possibly afford. (shrink)

How do people reason about their opponent in turn-taking games? Often, people do not make the decisions that game theory would prescribe. We present a logic that can play a key role in understanding how people make their decisions, by delineating all plausible reasoning strategies in a systematic manner. This in turn makes it possible to construct a corresponding set of computational models in a cognitive architecture. These models can be run and fitted to the participants’ data in terms (...) of decisions, response times, and answers to questions. We validate these claims on the basis of an earlier game-theoretic experiment about the turn-taking game “Marble Drop with Surprising Opponent”, in which the opponent often starts with a seemingly irrational move. We explore two ways of segregating the participants into reasonable “player types”. The first way is based on latent class analysis, which divides the players into three classes according to their first decisions in the game: Random players, Learners, and Expected players, who make decisions consistent with forward induction. The second way is based on participants’ answers to a question about their opponent, classified according to levels of theory of mind: zero-order, first-order and second-order. It turns out that increasing levels of decisions and theory of mind both correspond to increasing success as measured by monetary awards and increasing decision times. Next, we use the logical language to express different kinds of strategies that people apply when reasoning about their opponent and making decisions in turn-taking games, as well as the ‘reasoning types’ reflected in their behavior. Then, we translate the logical formulas into computational cognitive models in the PRIMs architecture. Finally, we run two of the resulting models, corresponding to the strategy of only being interested in one’s own payoff and to the myopic strategy, in which one can only look ahead to a limited number of nodes. It turns out that the participant data fit to the own-payoff strategy, not the myopic one. The article closes the circle from experiments via logic and cognitive modelling back to predictions about new experiments. (shrink)

In which respects do modeling and experimenting resemble or differ from each other? We explore this question through studying in detail the combinatorial strategy in synthetic biology whereby scientists triangulate experimentation on model organisms, mathematical modeling, and synthetic modeling. We argue that this combinatorial strategy is due to the characteristic constraints of the three epistemic activities. Moreover, our case study shows that in some cases materiality clearly matters, in fact it provides the very rationale of synthetic modeling. We will show (...) how the materialities of the different kinds of models – biological components versus mathematical symbols – in combination with their different structures – the complexity of biological organisms versus the isolated network structure and its mathematical dynamics - define the spectrum of epistemic possibilities in synthetic biology. Furthermore, our case shows that from the perspective of scientific practice the question of whether or not simulations are like or unlike experiments is often beside the point, since they are used to accomplish different kinds of things. (shrink)

This paper contrasts and compares strategies of model-building in condensed matter physics and biology, with respect to their alleged unequal susceptibility to trade-offs between different theoretical desiderata. It challenges the view, often expressed in the philosophical literature on trade-offs in population biology, that the existence of systematic trade-offs is a feature that is specific to biological models, since unlike physics, biology studies evolved systems that exhibit considerable natural variability. By contrast, I argue that the development of ever more sophisticated (...) experimental, theoretical, and computational methods in physics is beginning to erode this contrast, since condensed matter physics is now in a position to measure, describe, model, and manipulate sample-specific features of individual systems – for example at the mesoscopic level – in a way that accounts for their contingency and heterogeneity. Model-building in certain areas of physics thus turns out to be more akin to modeling in biology than has been supposed and, indeed, has traditionally been the case. (shrink)

Although the interdisciplinary nature of contemporary biological sciences has been addressed by philosophers, historians, and sociologists of science, the different ways in which engineering concepts and methods have been applied in biology have been somewhat neglected. We examine - using the mechanistic philosophy of science as an analytic springboard - the transfer of network methods from engineering to biology through the cases of two biology laboratories operating at the California Institute of Technology. The two laboratories study gene regulatory networks, but (...) in remarkably different ways. The research strategy of the Davidson lab fits squarely into the traditional mechanist philosophy in its aim to decompose and reconstruct, in detail, gene regulatory networks of a chosen model organism. In contrast, the Elowitz lab constructs minimal models that do not attempt to represent any particular naturally evolved genetic circuits. Instead, it studies the principles of gene regulation through a template-based approach that is applicable to any kinds of networks, whether biological or not. We call for the mechanists to consider whether the latter approach can be accommodated by the mechanistic approach, and what kinds of modifications it would imply for the mechanistic paradigm of explanation, if it were to address modelling more generally. (shrink)

The concept of sustainable development considers environmental, social and economic issues in general. And the goals of resource conservation and socio-economic development do not contradict each other, but contribute to mutual reinforcement. The purpose of this study is to build and test an economic and mathematical model for the formation of strategies for the behavior of an economic entity with an increase in the impact of negative environmental factors. The proposed strategies and their models are based on the (...) income-expenditure balance equation, which takes into account both quantitative and qualitative characteristics. The constructed models are considered in the state space. The research methodology is based on building models in the form of linear combinations of functions of a homogeneous external impact and various spatial combinations of economic sources (sinks). The study makes it possible to assess the dependence of the amount of resources used for life support on the chosen adaptive strategy. Within the framework of the proposed model, it was found that the criterion for the effectiveness of the applied strategy can be an indicator of satisfaction with the state, the preservation of which, simultaneously with the preservation of the size of resources used, corresponds to the direction of optimization. This approach is consistent with the concept of sustainable development. (shrink)

Theoretical models are an important tool for many aspects of scientific activity. They are used, i.a., to structure data, to apply theories or even to construct new theories. But what exactly is a model? It turns out that there is no proper definition of the term "model" that covers all these aspects. Thus, I restrict myself here to evaluate the function of models in the research process while using "model" in the loose way physicists do. To this end, I distinguish (...) four kinds of models. These are (1) models as special theories, (2) models as a substitute for a theory, (3) toy models and (4) developmental models. I argue that models of the types (3) and (4) are considerably useful in the process of theory construction. This will be demonstrated in an extended case-study from High-Energy Physics. (shrink)

ABSTRACT The article presents an attempt to analyze the strategic perspective of discourse, applying Critical Discourse Analysis (CDA) concepts and Crisis Communication analytical tools. The study aims to reveal key strategies employed by a political actor to form public perception while communicating a crisis, based on Donald Trump’s discourse on the COVID-19 pandemic. Results suggest four groups of strategies: (1) legitimization (through emotions, altruism, a hypothetical future, voices of expertise, rationality, defeasibility, simple denial and bolstering), (2) delegitimization (through (...) negative evaluations, accusations, sarcasm, nicknaming, attacking the accuser, shifting the blame), (3) mitigation (transcendence and differentiation) and (4) intensification (through the use of repetitions, metaphors, superlatives, intensifiers). The research concludes that the macro goal underlying the described strategies is to present the Trump administration’s efforts to address the COVID-19 pandemic as hard and effective. The study illustrates the use of language to model public perception and construct meaning in the context of a crisis. The research findings contribute to prior scientific inquiry into discursive strategies through suggesting a more comprehensive typology and extending CDA classifications by Crisis Communication categories. (shrink)

The development of new theory is often spurred by novel techniques that provide better answers to existing questions, or that allow asking new ones. In the field of strategy and organization science, models of complex adaptive systems have renewed theoretical work on a fundamental question: how organizations can adapt effectively to their environments. This article has three objectives: to highlight some areas where models of organizations as complex adaptive systems have made substantial contributions: the search for solutions to sets of (...) interdependent choices, the challenge of balancing processes of exploration and exploitation, and the organization of imperfect decision makers; to point to several challenges and tradeoffs which can limit the explanatory power and eventual impact of the modeling enterprise; and to sketch out possible future directions of research that would do further justice to the notion of organizations as complex adaptive systems. (shrink)

This paper is an interpretation and defense of Richard Levins’ “The Strategy of Model Building in Population Biology,” which has been extremely influential among biologists since its publication 40 years ago. In this article, Levins confronted some of the deepest philosophical issues surrounding modeling and theory construction. By way of interpretation, I discuss each of Levins’ major philosophical themes: the problem of complexity, the brute-force approach, the existence and consequence of tradeoffs, and robustness analysis. I argue that Levins’ article is (...) concerned, at its core, with justifying the use of multiple, idealized models in population biology. (shrink)

There is a rapidly growing interest in the topic of sustainability as it relates to long‐term business performance that optimizes the “triple bottom line”: economic, environmental, and social outcomes. This article articulates a multilevel conceptual model for executing a business strategy for sustainability primarily through the design and implementation of human resource management practices. The model builds on open systems theory, the resource based view of the firm, and the concept of line of sight to identify certain key organizational capabilities, (...) group competencies, and individual abilities and other characteristics that combine to drive organizational performance when pursuing a sustainability strategy. The article concludes with a discussion of implications of the model for theory, research, and practice. (shrink)

Some how-possibly explanations have epistemic value because they are epistemically possible; we cannot rule out their truth. One paradoxical implication of that proposal is that epistemic value may be obtained from mere ignorance. For the less we know, then the more is epistemically possible. This chapter examines a particular class of problematic epistemically possible how-possibly explanations, viz. *epistemically opaque* how-possibly explanations. Those are how-possibly explanations justified by an epistemically opaque process. How could epistemically opaque how-possibly explanations have epistemic value if (...) they result from a process about which we lack knowledge or understanding? This chapter proposes three different strategies to salvage epistemic value from epistemic opacity, namely salvaging value from 1) functional transparency, 2) modal operator interpretation, and 3) pursuitworthiness. It illustrates using cases from deep neural network modeling. (shrink)

ABSTRACT Is there something specific about modelling that distinguishes it from many other theoretical endeavours? We consider Michael Weisberg’s thesis that modelling is a form of indirect representation through a close examination of the historical roots of the Lotka–Volterra model. While Weisberg discusses only Volterra’s work, we also study Lotka’s very different design of the Lotka–Volterra model. We will argue that while there are elements of indirect representation in both Volterra’s and Lotka’s modelling approaches, they are largely (...) due to two other features of contemporary model construction processes that Weisberg does not explicitly consider: the methods-drivenness and outcome-orientedness of modelling. 1Introduction 2Modelling as Indirect Representation 3The Design of the Lotka–Volterra Model by Volterra 3.1Volterra’s method of hypothesis 3.2The construction of the Lotka–Volterra model by Volterra 4The Design of the Lotka–Volterra Model by Lotka 4.1Physical biology according to Lotka 4.2Lotka’s systems approach and the Lotka–Volterra model 5Philosophical Discussion: Strategies and Tools of Modelling 5.1Volterra’s path from the method of isolation to the method of hypothesis 5.2The template-based approach of Lotka 5.3Modelling: methods-driven and outcome-oriented 6Conclusion. (shrink)

In this study we relate four different measures: the theodicy models proposed by van der Ven, the coping strategies proposed by Pargament, a measure of positive or negative self-image and the post critical belief scales we ourselves have developed. We analysed the data of 251 Dutch-speaking Belgians. In the analysis we focus on the relation of the different measures with the post critical belief scales. Different types of believers are using different theodicy models, somewhat different coping strategies and (...) we observe some differences in self-image, where believers have a more positive self-image than non-believers. We could suggest that there is a specific theodicy model used by symbolic believers and another theodicy model used by more literal believers. The former could be interpreted as more developed and perhaps more religiously mature. (shrink)

This study aimed to explore practices and strategies that have successfully reduced time-to-proficiency of the workforce in large multinational organisations and develop a model based on them. The central research question of this study was: How can organisations accelerate time-to-proficiency of employees in the workplace? The study addressed three aspects: the meaning of accelerated proficiency, as seen by business leaders; the business factors driving the need for shorter time-to-proficiency and benefits accrued from it; and practices and strategies to (...) shorten time-to-proficiency of the workforce. 85 participants (n=85) from 7 countries who represented 10 economic sectors, 20 business sectors and 28 industry groups contributed 66 successful bounded project cases. A qualitative research approach was used. Data were collected through in-depth interviews with project leaders and by collecting additional project case documents. Data were analysed using thematic analysis to identify the themes in the data. Matrix analysis was then used to perform within-case and cross-case analysis to compare the project cases. 11 overarching themes were developed from the data analysis, out of which two overarching themes explained the characteristics of job-role proficiency and accelerated proficiency, while three overarching themes described the magnituide and scale of time-to-proficiency business problem, business drivers for accelerating proficiency and business benefits of reduced time-to-proficiency. Six overarching themes revealed the business practices employed by organisations to reduce time-to-proficiency: (1) Defining business-driven proficiency measures in terms of expected business outcomes from a job role; (2) Developing a proficiency reference map of all the inputs, conditions and roadblocks that determine or influence how required business outcomes are being produced in a job role; (3) Sequencing an efficient proficiency path of activities and experiences ordered to produce the desired business outcomes in the shortest possible time; (4) Manufacturing accelerated contextual experiences by leveraging on-the-job opportunities or training interventions in a compressed time-frame; (5) Promoting an active emotional immersion through engagements, consequences, stakes, feedback and proficiency assessments; and (6) Setting up a proficiency eco-system, providing timely support to performers while doing the job such as enabling job environment, highly involved manager, structured mentoring from experts, purposeful social connectivity with peers, leveraging subject matter experts and on-demand performance support systems. Organisations orchestrated these six business practices as an input-output-feedback system to reduce time-to-proficiency of the workforce. A conceptual model (Accelerated Proficiency Model) was developed representing interactions among six business-level practices/processes as a closed-loop system to explain the concept and process of accelerated proficiency in the workplace. These practices were implemented through a set of twenty-four strategies proven successful in various contexts. The strategies employed were much beyond the boundaries of conventional training interventions. The job itself acted as the primary mechanism to accelerate proficiency. A two-level hierarchical framework (6/24 framework of strategies) was also constructed in the form of a checklist consisting of six practices and twenty-four strategies for practitioners. Overall, the findings of this research study contribute significantly to the body of knowledge on accelerated proficiency. In particular, the conceptual model and the framework developed in this study can be implemented across a range of contexts, business sectors, job types and settings to reduce time-to-proficiency of the workforce. (shrink)

This article examines the growing public and professional concern with the diminished historical awareness among school children in contemporary Great Britain. Research concerning British responses to this perceived crisis was believed to be particularly pertinent to similar challenges facing the upgrading of the history curriculum in the United States. Extensive teaching and observation activities in British schools revealed a number of innovative strategies particularly concerned with the improvement of history instruction in the primary school. The activities seem to provide (...) valuable models for consideration for application to American elementary school history programs. (shrink)

In recent years, there has been increasing interest in investigating science communication. Some studies that address this issue attempt to develop a model to determine the level of confidence that an author or a scientific community has at a given time towards a theory or a group of theories. A well-established approach suggests that, in order to determine the level of certainty authors have with regard to the statements they make, one can identify specific lexical and morphosyntactical markers which indicate (...) their epistemic attitudes. This method is considered particularly appealing because it permits the development of an algorithmic model based on the quantitative analysis of the occurrence of these markers to assess automatically and objectively the opinion of an author or the predominant opinion of a scientific community on a topic at a given time. In this contribution we show that this line of research presents many kinds of problems especially when it is applied to research articles. To this aim, we propose two main lines of reasoning. The first one relies generally on the argumentative structure of scientific articles and shows that certainty/uncertainty markers are used differently in different argument forms and that therefore their number/frequency of use does not offer reliable indications for determining whether the topic at issue is considered by the authors to be more or less factual/speculative. The second one is based on the analysis of a sample of psychiatric research articles on homosexuality written over a long time span and taken from The British Journal of Psychiatry. Since the psychiatric perspective on homosexuality changed radically during the decades in which these articles were published, they offer an inventory of various kinds of argumentative strategies directed both at defending and confuting dominant as well as marginal positions. We focus especially on uncertainty markers and show that frequently the positions stated using expressions indicating uncertainty are actually not considered as conjectural or speculative by their authors, but that the use of uncertainty markers is motivated by a number of different and often incongruent rhetorical strategies. (shrink)

This research presents a computer model called EUREKA that begins with novice‐like strategies and knowledge organizations for solving physics word problems and acquires features of knowledge organizations and basic approaches that characterize experts in this domain. EUREKA learns a highly interrelated network of problem‐type schemas with associated solution methodologies. Initially, superficial features of the problem statement form the basis for both the problem‐type schemas and the discriminating features that organize them in the P‐MOP (Problem Memory Organization Packet) network. As (...) EUREKA solves more problems, the content of the schemas and the discriminating features change to reflect more fundamental physics principles. This changing network allows EUREKA to shift from a novicelike means‐ends strategy to a more expertlike “knowledge development” strategy in which the presence of abstract concepts are triggered by problem features. In this model, the strategy shift emerges as a natural consequence of the evolving expertlike organization of problem‐type schemos. EUREKA captures many of the descriptive models of novice expert differences, and also suggests a number of empirically testable assumptions regarding problem‐solving strategies and the representation of problem‐solving knowledge. (shrink)

Pluripotency can be considered a functional characteristic of pluripotent stem cells (PSCs) populations and their niches, rather than a property of individual cells. In this view, individual cells within the population independently adopt a variety of different expression states, maintained by different signaling, transcriptional, and epigenetics regulatory networks. In this review, we propose that generation of integrative network models from single cell data will be essential for getting a better understanding of the regulation of self‐renewal and differentiation. In particular, we (...) suggest that the identification of network stability determinants in these integrative models will provide important insights into the mechanisms mediating the transduction of signals from the niche, and how these signals can trigger differentiation. In this regard, the differential use of these stability determinants in subpopulation‐specific regulatory networks would mediate differentiation into different cell fates. We suggest that this approach could offer a promising avenue for the development of novel strategies for increasing the efficiency and fidelity of differentiation, which could have a strong impact on regenerative medicine. (shrink)

El artículo muestra una estrategia metodológica para garantizar la dirección del proceso educativo para el desarrollo de la habilidad intelectual modelación en los estudiantes; devela sus principales fundamentos epistémicos, sus etapas y acciones esenciales. Para ello se aplicaron métodos científicos de investigación. La constatación de los resultados brinda evidencias positivas acerca de su pertinencia, al considerar el carácter coparticipativo y coprotagónico que adquieren las influencias educativas en el contexto institucional en la dirección de un proceso educativo único. The article shows (...) a methodological strategy to ensure the teaching process direction in order develop intellectual skill modeling in students; It reveals its main epistemic foundations, its stages and essential actions. That is the reason for which different research scientific methods were applied. Verification of results provides positive evidence of its pertinence when considering the collaborative nature of the educational influences within the institutional context in the direction of a unique educational process. (shrink)

When developing computational models to analyze the tradeoffs between climate risk management strategies (i.e., mitigation, adaptation, or geoengineering), scientists make explicit and implicit decisions that are influenced by their beliefs, values and preferences. Model descriptions typically include only the explicit decisions and are silent on value judgments that may explain these decisions. Eliciting scientists’ mental models, a systematic approach to determining how they think about climate risk management, can help to gain a clearer understanding of their modeling decisions. In (...) order to identify and represent the role of values, beliefs and preferences on decisions, we used an augmented mental models research approach, namely values-informed mental models (ViMM). We conducted and qualitatively analyzed interviews with eleven climate risk management scientists. Our results suggest that these scientists use a similar decision framework to each other to think about modeling climate risk management tradeoffs, including eight specific decisions ranging from defining the model objectives to evaluating the model’s results. The influence of values on these decisions varied between our scientists and between the specific decisions. For instance, scientists invoked ethical values (e.g., concerns about human welfare) when defining objectives, but epistemic values (e.g., concerns about model consistency) were more influential when evaluating model results. ViMM can (i) enable insights that can inform the design of new computational models and (ii) make value judgments explicit and more inclusive of relevant values. This transparency can help model users to better discern the relevance of model results to their own decision framing and concerns. (shrink)

How individuals tend to evaluate the combination of their own and other’s payoffs—social value orientations—is likely to be a potential target of future moral enhancers. However, the stability of cooperation in human societies has been buttressed by evolved mildly prosocial orientations. If they could be changed, would this destabilize the cooperative structure of society? We simulate a model of moral enhancement in which agents play games with each other and can enhance their orientations based on maximizing personal satisfaction. We find (...) that given the assumption that very low payoffs lead agents to be removed from the population, there is a broadly stable prosocial attractor state. However, the balance between prosociality and individual payoff-maximization is affected by different factors. Agents maximizing their own satisfaction can produce emergent shifts in society that reduce everybody’s satisfaction. Moral enhancement considerations should take the issues of social emergence into account. (shrink)

In an era of rising social awareness, both academics and practitioners have been concerned about the effectiveness of pro-social consumer influence strategies. The main assumption here is that for social marketing to succeed one must first understand the factors underlying pro-social consumer behavior. Firstly, drawing on two dimensions the authors first identify four types of social behavior. Next, the model describes social behavior as a result of preceding social behavior motivation and actual social behavior intention. Norms and economic evaluation (...) have an impact on social behavior motivation, which in turn influences social behavior intention, eventually leading to actual social behavior. Actual control factors, such as the availability of resources and opportunities, decide whether social behavior intention can really translate into actual social behavior. Finally, authors propose message strategies for each type of social behavior. (shrink)

Computational modeling of the brain holds great promise as a bridge from brain to behavior. To fulfill this promise, however, it is not enough for models to be 'biologically plausible': models must be structurally accurate. Here, we analyze what this entails for so-called psychobiological models, models that address behavior as well as brain function in some detail. Structural accuracy may be supported by (1) a model's a priori plausibility, which comes from a reliance on evidence-based assumptions, (2) fitting existing data, (...) and (3) the derivation of new predictions. All three sources of support require modelers to be explicit about the ontology of the model, and require the existence of data constraining the modeling. For situations in which such data are only sparsely available, we suggest a new approach. If several models are constructed that together form a hierarchy of models, higher-level models can be constrained by lower-level models, and low-level models can be constrained by behavioral features of the higher-level models. Modeling the same substrate at different levels of representation, as proposed here, thus has benefits that exceed the merits of each model in the hierarchy on its own. (shrink)

This paper examines creative strategies employed inscientific modelling. It is argued that being creativepresents not a discrete event, but rather an ongoingeffort consisting of many individual `creative acts''.These take place over extended periods of time andcan be carried out by different people, working ondifferent aspects of the same project. The example ofextended extragalactic radio sources shows that, inorder to model a complicated phenomenon in itsentirety, the modelling task is split up into smallerproblems that result in several sub-models. (...) This is away of using cognitive resources efficiently and in away which overcomes their limitations. Another aspectof modelling that requires creativity is theemployment of visualisation in order to reassemble,i.e. recreate the unity of, the various sub-models bymeans of visualisation. This illustrates how thecreative effort required to deal with the complexityof the complicated phenomenon of radio sources ischannelled in order to use cognitive resourcesefficiently and to stay within their capacity. (shrink)

The paper advances a realist analytical model for case studies of national soft power policies. First, it argues that for the purposes of realist analysis, a soft power policy must be considered as a rational strategy pursued under the conditions of competition. Furthermore, it emphasises the importance of taking into account the specificities of the recipient state as well as the fact that a soft power strategy is targeted at both its elite and its public. In addition, the article substantiates (...) the necessity to draw a clear-cut distinction between soft power sources and instruments and shows possible shortcomings that research can have should this distinction fail to be made. Finally, the paper discusses the impact of a competitor’s presence on a soft power strategy and specifies the terms under which disregarding this impact may engender a wrong conclusion. (shrink)

Controversial industry sectors, such as alcohol, gambling, and tobacco, though long-established, suffer organizational legitimacy problems. The authors consider various strategies used to seek organizational legitimacy in the U.K. casino gambling market. The findings are based on a detailed, multistakeholder case study pertaining to a failed bid for a regional supercasino. They suggest four generic strategies for seeking organizational legitimacy in this highly complex context: construing, earning, bargaining, and capturing, as well as pathways that combine these strategies. The (...) case analysis and proposed bidimensional model of generic legitimacy-seeking strategies contribute to limited literature on organizational legitimacy in controversial industry sectors. In addition, beyond organizations active in controversial contexts, this study and its implications are useful for individuals and organizations supporting or opposing the organizational legitimacy of organizations in controversial industries. (shrink)

A study of the rhetorical and political strategy adopted by the Roman orator and statesman Cicero as a newcomer in Roman republican politics. Henriette van der Blom argues that Cicero advertised himself as a follower of chosen models of behaviour from the past - his role models - and in turn presented himself as a role model to others.