Abstract.Since the gene splicing debates of the 1980s, the public has been exposed to an ongoing sequence of genetic and reproductive technologies. Many issue areas have outcomes that lose track of people's inner values or engender opposing religious viewpoints defying final resolution. This essay relocates the discussion of what is an acceptable application from the individual to the societal level, examining technologies that stand to address large numbers of people and thus call for policy resolution, rather than individual fiat, in (...) their application. A major source of guidance is the “Genetic Frontiers” series of professional dialogues and conferences held by the National Conference for Community and Justice from 2002 to 2004. Genetic testing, human gene therapy, genetic engineering of plants and animals, and stem cell technology are examined. While differences in perspective on the beginning of life persist, a stepwise approach to the examination of genetic testing reveals areas of general agreement. Stewardship of life, human co‐creativity with the divine, and social justice help define the bounds of application of genetic engineering and therapy; compassionate care plays a major role in establishing stem cell policy. Active, sustained dialogue is a useful resource for enabling sharing of religious values and crystallization of policies. (shrink)

The ability to convert human somatic cells into induced pluripotent stem cells (iPSCs) is allowing the production of custom‐tailored cells for drug discovery and for the study of disease phenotypes at the cellular and molecular level. IPSCs have been derived from patients suffering from a large variety of disorders with different severities. In many cases, disease related phenotypes have been observed in iPSCs or their lineage‐specific progeny. Several proof of concept studies have demonstrated that these phenotypes can be reversed in (...) vitro using approved drugs. However, several challenges must be overcome to take full advantage of this technology. Here, we highlight recent advances in the field and discuss the main challenges associated with this technology as it applies to disease modelling. (shrink)

Reference models of the earth’s interior play an important role in the acquisition of knowledge about the earth’s interior and the earth as a whole. Such models are used as a sort of standard reference against which data are compared. I argue that the use of reference models merits more attention than it has gotten so far in the literature on models, for it is an example of a method of doing science that has a long and significant history, and (...) a study of reference models could increase our understanding of this methodology. (shrink)

This paper explores the epistemic status of models and simulations between theory, on the one hand, and observations, on the other. In particular, I will argue that the interpretation of an essentially invariant astrophysical model structure can change substantially over time. I will illustrate this claim using as an example the first 20 years (1985–2004) of development of the Paris-Durham shock code—a numerical model of slow interstellar shock waves (i.e. a disturbance of the medium that travel faster than (...) the local speed of sound). I will show that the model’s interpretation and, in particular, its underlying representational ideal—the modeler’s (often implicit) goal governing the development and the use of the model—changed notably during this period. Whereas the code was originally used in a purely exploratory fashion, it was later taken to represent and encompass the target phenomenon as completely as possible. It is noteworthy that during this transition the model’s change of epistemic status was never explicitly acknowledged or in any way articulated. However, the impetus for the change can, I claim, be found in the role that observational data came to play in the later publications. (shrink)

In the present study, ordinary kriging and support vector machine have been used to develop three dimensional site characterization model of an alluvial site based on standard penetration test results. The SVM is a novel type of learning machine based on statistical learning theory, uses regression technique by introducing ε-insensitive loss function has been adopted. The knowledge of the semivariogram of the SPT values is used in the ordinary kriging method to predict the N values at any point in (...) the subsurface of the site where field measurements are not available. The comparison between the SVM and ordinary kriging model demonstrates that the SVM model is superior to ordinary kriging model in predicting N values in the site. (shrink)

It is a hallmark of a good model to make accurate a priori predictions to new conditions (Busemeyer & Wang, 2000). This study compared 8 decision learning models with respect to their generalizability. Participants performed 2 tasks (the Iowa Gambling Task and the Soochow Gambling Task), and each model made a priori predictions by estimating the parameters for each participant from 1 task and using those same parameters to predict on the other task. Three methods were used to (...) evaluate the models at the individual level of analysis. The first method used a post hoc fit criterion, the second method used a generalization criterion for short‐term predictions, and the third method again used a generalization criterion for long‐term predictions. The results suggest that the models with the prospect utility function can make generalizable predictions to new conditions, and different learning models are needed for making short‐versus long‐term predictions on simple gambling tasks. (shrink)

This paper explores the epistemic status of models and simulations between theory, on the one hand, and observations, on the other. In particular, I will argue that the interpretation of an essentially invariant astrophysical model structure can change substantially over time. I will illustrate this claim using as an example the first 20 years (1985–2004) of development of the Paris-Durham shock code—a numerical model of slow interstellar shock waves (i.e. a disturbance of the medium that travel faster than (...) the local speed of sound). I will show that the model’s interpretation and, in particular, its underlying representational ideal—the modeler’s (often implicit) goal governing the development and the use of the model—changed notably during this period. Whereas the code was originally used in a purely exploratory fashion, it was later taken to represent and encompass the target phenomenon as completely as possible. It is noteworthy that during this transition the model’s change of epistemic status was never explicitly acknowledged or in any way articulated. However, the impetus for the change can, I claim, be found in the role that observational data came to play in the later publications. (shrink)

ArgumentIt seems theoretically convenient to construe knowledge practices in financial markets and organizations as “applied economics.” Alternatively or additionally, one might argue that practitioners draw on economic knowledge in order to systematically orient their actions towards profit-maximization; models, then, are understood as devices that make calculative rationality possible. However, empirical studies do not entirely confirm these theoretical positions: Practitioners’ actual calculations are often not “framed” by models; organizations and institutions influence the choice and adoption of models; and different professional groups (...) in financial markets have diverging attitudes towards model calculations. In order to account for this diversity, this article proposes the concept ofcultures of economic and financial expertise; the concept focuses on the patterns of knowledge practices and knowledge-related self-definitions of groups within financial organizations and markets; it also facilitates an analysis of the relations between and, more specifically, the hierarchies among different practices and identities. The article then goes on to explore the process of foreign exchange forecasting in a particular bank. The description immediately reveals that two groups are involved in this process: economists and analysts. These groups maintain quite different practices and self-descriptions in relation to models: While the economists in the bank use the models as organizational resources for consistent forecasting procedures and observe data with the help of simple model structures, analysts approach model forecasts from the perspective of critics: They see limits in the variable-centered, as opposed to a “thematic” approach and they disregard a model's imposed temporality. Nevertheless, analysts use model forecasts as anchors for developing their own “paths” and stories about possible future expectation changes in the markets. The specific division of labor between economists and analysts, and specifically the dominant role of analysts in the forecasting process, fit into a larger picture: The rise of institutional investors in the foreign exchange markets and their demand for genuine market knowledge for speculative investment projects has contributed to the rise and dominance of analysts’ culture. (shrink)

Due to the increasing number of people traveling by air, the passenger flow at the airport is increasing, and the problem of passenger drop-off and pickup has a huge impact on urban traffic. The difficulty of taking a taxi at the airport is still a hot issue in the society. Aiming at the problem of optimizing the allocation of taxi resource, this paper is based on the cost-benefit analysis method to determine the factors that affect the taxi driver’s decision-making. The (...) mathematical methods such as function equation, BP neural network algorithm, and queuing theory were used to establish a complete decision-making model for taxi drivers and an optimization model of dispatching efficiency at the airport. A conclusion has been drawn that the allocation of airport taxi resource should be arranged closely related to drivers’ revenue and the layout of airport line. (shrink)

One approach to validating simulation models is to formally compare model outputs with independent data. We consider such model validation from the point of view of Frequentist statistics. A range of estimates and tests of goodness of fit have been advanced. We review these approaches, and demonstrate that some of the tests suffer from difficulties in interpretation because they rely on the null hypothesisHypothesis that the model is similar to the observationsObservations. This reliance creates two unpleasant possibilities, (...) namely, a model could be spuriously validated when dataData are too few, or inappropriately rejected when data are too many. Finally, these tests do not allow a principled declaration of what a reasonable level of difference would be considering the purposes to which the model will be put. We consider equivalence tests, and demonstrate that they do not suffer from the previously identified shortcomings. We provide two case studies to illustrate the claims of the chapter. (shrink)

We propose a new approach for tracing value change. Value change may lead to a mismatch between current value priorities in society and the values for which technologies were designed in the past, such as energy technologies based on fossil fuels, which were developed when sustainability was not considered a very important value. Better anticipating value change is essential to avoid a lack of social acceptance and moral acceptability of technologies. While value change can be studied historically and qualitatively, we (...) propose a more quantitative approach that uses large text corpora. It uses probabilistic topic models, which allow us to trace values that are latent. We demonstrate the approach for five types of value change in technology. Our approach is useful for testing hypotheses about value change, such as verifying whether value change has occurred and identifying patterns of value change. The approach can be used to trace value change for various technologies and text corpora, including scientific articles, newspaper articles, and policy documents. (shrink)

Emotional design is an important development trend of interaction design. Emotional design in products plays a key role in enhancing user experience and inducing user emotional resonance. In recent years, based on the user's emotional experience, the design concept of strengthening product emotional design has become a new direction for most designers to improve their design thinking. In the emotional interaction design, the machine needs to capture the user's key information in real time, recognize the user's emotional state, and use (...) a variety of clues to finally determine the appropriate user model. Based on this background, this research uses a deep learning mechanism for more accurate and effective emotion recognition, thereby optimizing the design of the interactive system and improving the user experience. First of all, this research discusses how to use user characteristics such as speech, facial expression, video, heartbeat, etc., to make machines more accurately recognize human emotions. Through the analysis of various characteristics, the speech is selected as the experimental material. Second, a speech-based emotion recognition method is proposed. The mel-Frequency cepstral coefficient of the speech signal is used as the input of the improved long and short-term memory network. To ensure the integrity of the information and the accuracy of the output at the next moment, ILSTM makes peephole connections in the forget gate and input gate of LSTM, and adds the unit state as input data to the threshold layer. The emotional features obtained by ILSTM are input into the attention layer, and the self-attention mechanism is used to calculate the weight of each frame of speech signal. The speech features with higher weights are used to distinguish different emotions and complete the emotion recognition of the speech signal. Experiments on the EMO-DB and CASIA datasets verify the effectiveness of the model for emotion recognition. Finally, the feasibility of emotional interaction system design is discussed. (shrink)

Excessive use of social media is a developing concern in the twenty-first century. This issue needs to be addressed before it has any more significant consequences than what we are currently experiencing. As a preventive technique, advertisements and awareness-raising campaigns about the detrimental impact of digital technologies are used. The application of novel mathematical techniques and terminologies in this field of study will have significant potential to enhance healthy living by preventing certain ailments. This is the most compelling justification for (...) conducting a new study with the most up-to-date techniques at our disposal. This study investigates clear and concise transmission in order to generate a deterministic mathematical model of social media addiction S M A using the fractal-fractional derivative operator. Also, the analysis of the S M A model in terms of the invariant domain, the existence of a positive invariant solution, and equilibria assumptions are stated in a detailed manner. Besides that, the basic reproduction number ℝ 0 < 1 is computed, demonstrating that the proposed methodology is more efficacious. The Atangana-Baleanu FF differential operators are recently defined in FF differential operators that are applied to characterize the S M A model’s mathematical algorithm. We investigated the numerical behaviour of the S M A in three ways: changing the fractional-order α as well as the fractal-dimension ℘ ; changing α while keeping ℘ constant; and changing ℘ while keeping α constant. Our examined visualizations and simulation studies using MATLAB for the numerical modelling of the aforementioned system showed that the novel developed Atangana-Baleanu FF differential operators produce remarkable results when compared to the classical frame. (shrink)

In air traffic control, the airspace is divided into several smaller sectors for better management of air traffic and air traffic controller workload. Such sectors are usually managed by a team of two air traffic controllers: planning controller and executive controller. D-side controller is responsible for processing flight-plan information to plan and organize the flow of traffic entering the sector. R-side controller deals with ensuring safety of flights in their sector. A better understanding and predictability of D-side controller actions, for (...) a given traffic scenario, may help in automating some of its tasks and hence reduce workload. In this paper, we propose a learning model to predict D-side controller actions. The learning problem is modeled as a supervised learning problem, where the target variables are D-side controller actions and the explanatory variables are the aircraft 4D trajectory features. The model is trained on six months of ADS-B data over an en-route sector, and its generalization performance was assessed, using crossvalidation, on the same sector. Results indicate that the model for vertical maneuver actions provides highest prediction accuracy. Besides, the model for speed change and course change action provides predictability accuracy of 80% and 87%, respectively. The model to predict the set of all the actions for each flight achieves an accuracy of 70% implying for 70% of flights; D-side controller’s action can be predicted from trajectory information at sector entry position. In terms of operational validation, the proposed approach is envisioned as ATCO assisting tool, not an autonomous tool. Thus, there is always ATCO discretion element, and as more ATCO actions are collected, the models can be further trained for better accuracy. For future work, we will consider expanding the feature set by including parameters such as weather and wind. Moreover, human in the loop simulation will be performed to measure the effectiveness of the proposed approach. (shrink)

Despite an enormous philosophical literature on models in science, surprisingly little has been written about data models and how they are constructed. In this paper, I examine the case of how paleodiversity data models are constructed from the fossil data. In particular, I show how paleontologists are using various model-based techniques to correct the data. Drawing on this research, I argue for the following related theses: first, the ‘purity’ of a data model is not a measure of its (...) epistemic reliability. Instead it is the fidelity of the data that matters. Second, the fidelity of a data model in capturing the signal of interest is a matter of degree. Third, the fidelity of a data model can be improved ‘vicariously’, such as through the use of post hoc model-based correction techniques. And, fourth, data models, like theoretical models, should be assessed as adequate for particular purposes. (shrink)

We describe a new approach for developing and validating cognitive process models. We develop graphical models (specifically, hidden Markov models) both from human empirical data on a task, as well as from synthetic data traces generated by a cognitive process model of human behavior on the task. We show that considering differences between the two graphical models can unveil substantive and nuanced imperfections of cognitive process models that can then be addressed to increase their fidelity to empirical data.

Most recent philosophical thought about the scientific representation of the world has focused on dyadic relationships between language-like entities and the world, particularly the semantic relationships of reference and truth. Drawing inspiration from diverse sources, I argue that we should focus on the pragmatic activity of representing, so that the basic representational relationship has the form: Scientists use models to represent aspects of the world for specific purposes. Leaving aside the terms "law" and "theory," I distinguish principles, specific conditions, models, (...) hypotheses, and generalizations. I argue that scientists use designated similarities between models and aspects of the world to form both hypotheses and generalizations. (shrink)

Drinking kills a significant proportion of individuals every year, particularly in low-income communities. An impulsive differential equation system is used to explore the effectiveness of activated charcoal in detoxifying the body after methanol poisoning. Our impression of activated charcoal is shaped by the fractional dynamics of the problem, which leads to speedy and low-cost first aid. The adsorption capacity of activated charcoal is investigated using impulsive differential equations. The ABC fractional operator’s findings paint a more realistic image of first aid (...) in public and primary health centers, which can assist to reduce methanol poisoning deaths. Numerical simulations are provided using generalized Adams–Bashforth–Moulton method. (shrink)

In this research, the He-Laplace algorithm is extended to generalized third order, time-fractional, Korteweg-de Vries models. In this algorithm, the Laplace transform is hybrid with homotopy perturbation and extended to highly nonlinear fractional KdVs, including potential and Burgers KdV models. Time-fractional derivatives are taken in Caputo sense throughout the manuscript. Convergence and error estimation are confirmed theoretically as well as numerically for the current model. Numerical convergence and error analysis is also performed by computing residual errors in the entire (...) fractional domain. Graphical illustrations show the effect of fractional parameter on the solution as 2D and 3D plots. Analysis reveals that the He-Laplace algorithm is an efficient approach for time-fractional models and can be used for other families of equations. (shrink)

The crime is difficult to predict; it is random and possibly can occur anywhere at any time, which is a challenging issue for any society. The study proposes a crime prediction model by analyzing and comparing three known prediction classification algorithms: Naive Bayes, Random Forest, and Gradient Boosting Decision Tree. The model analyzes the top ten crimes to make predictions about different categories, which account for 97% of the incidents. These two significant crime classes, that is, violent and (...) nonviolent, are created by merging multiple smaller classes of crimes. Exploratory data analysis is performed to identify the patterns and understand the trends of crimes using a crime dataset. The accuracies of Naive Bayes, Random Forest, and Gradient Boosting Decision Tree techniques are 65.82%, 63.43%, and 98.5%, respectively, and the proposed model is further evaluated for precision and recall matrices. The results show that the Gradient Boosting Decision Tree prediction model is better than the other two techniques for predicting crime, based on historical data from a city. The analysis and prediction model can help the security agencies utilize the resources efficiently, anticipate the crime at a specific time, and serve society well. (shrink)

Parameters of a Bertalanffy type of temperature dependent growth model are fitted using data from a population of stone loach ( Barbatula barbatula ). Over two periods respectively in 1990 and 2010 length data of this population has been collected at a lowland stream in the central part of the Netherlands. The estimation of the maximum length of a fully grown individual is given special attention because it is in fact found as the result of an extrapolation over a (...) large interval of the entire lifetime. It is concluded that this parameter should not at forehand be set at one fixed value for the population at that location due to varying conditions over the years. (shrink)

This paper provides a general introduction to the use of causal models in the metaphysics of causation, specifically structural equation models and directed acyclic graphs. It reviews the formal framework, lays out a method of interpretation capable of representing different underlying metaphysical relations, and describes the use of these models in analyzing causation.

Scientific models may be more useful for false assumptions they make than true ones when one is interested not in the fit of the model, but in the form of the residuals. Modeling Darwin's “blending” theory of inheritance shows how it illuminates features of Mendelian theory. Insufficient understanding of it leads to incorrect moves in modeling population structure. But it may prove even more useful for organizing a theory of cultural evolution. Analysis of “blending” inheritance gives new tools for (...) recognizing population structure for culture and for understanding differences between biological and cultural inheritance. (shrink)

This study aims to use the Asian knowledge model “APO” as a determinant for performance excellence in universities and identifying the most effecting factors on it. This study was applied on Al-Azhar University in Gaza strip. The result of the study showed that (APO) model is valid as a measure and there are four dimensions in the model affecting significantly more than the others (university processes, KM leadership, personnel, KM outputs). Furthermore, performance excellence produced though modernizing the (...) means of education, curriculum development, technology and flexibility in the organizational structure. The study recommends expanding the usage of (APO) model, enhancing the role of knowledge leadership, technology, organizational flexibility, sharing culture and incentive systems that encouraging innovation. (shrink)

We employ an infinite-signature Hrushovski amalgamation construction to yield two results in Recursive Model Theory. The first result, that there exists a strongly minimal theory whose only recursively presentable models are the prime and saturated models, adds a new spectrum to the list of known possible spectra. The second result, that there exists a strongly minimal theory in a finite language whose only recursively presentable model is saturated, gives the second non-trivial example of a spectrum produced in a (...) finite language. (shrink)

This paper discusses critically what simulation models of the evolution of cooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” (1984) and the modeling tradition it has inspired. Hardly any of the many simulation models in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. But this research design was fundamentally flawed. (...) At best such simulations can claim to prove logical possibilities, i.e. they prove that certain phenomena are possible as the consequence of the modeling assumptions built into the simulation, but not that they are possible or can be expected to occur in reality. I suggest several requirements under which proofs of logical possibilities can nevertheless be considered useful. Sadly, most Axelrod-style simulations do not meet these requirements. It would be better not to use this kind of simulations at all. (shrink)

Action Languages are formal methods of talking about actions and their effects on fluents. One recent approach in planning is to define the domains of the planning problems using action languages. The aim of this research is to find a plan for a system defined in the action language C by translating it into a causal theory and then finding an equivalent logic program. The planning problem will then be reduced to finding the answer set (stable model) of this (...) logic program. This planner will be added as an extension to the Causal Calculator (CCALC) which is a model checker for the language of the causal theories. (shrink)

This paper discusses critically what simulation models of the evolution ofcooperation can possibly prove by examining Axelrod’s “Evolution of Cooperation” and the modeling tradition it has inspired. Hardly any of the many simulation models of the evolution of cooperation in this tradition have been applicable empirically. Axelrod’s role model suggested a research design that seemingly allowed to draw general conclusions from simulation models even if the mechanisms that drive the simulation could not be identified empirically. But this research design (...) was fundamentally flawed, because it is not possible to draw general empirical conclusions from theoretical simulations. At best such simulations can claim to prove logical possibilities, i.e. they prove that certain phenomena are possible as the consequence of the modeling assumptions built into the simulation, but not that they are possible or can be expected to occur in reality I suggest several requirements under which proofs of logical possibilities can nevertheless be considered useful. Sadly, most Axelrod-style simulations do not meet these requirements. I contrast this with Schelling’s neighborhood segregation model, thecore mechanism of which can be retraced empirically. (shrink)

Bayesian models of legal arguments generally aim to produce a single integrated model, combining each of the legal arguments under consideration. This combined approach implicitly assumes that variables and their relationships can be represented without any contradiction or misalignment, and in a way that makes sense with respect to the competing argument narratives. This paper describes a novel approach to compare and ‘average’ Bayesian models of legal arguments that have been built independently and with no attempt to make them (...) consistent in terms of variables, causal assumptions or parameterization. The approach involves assessing whether competing models of legal arguments are explained or predict facts uncovered before or during the trial process. Those models that are more heavily disconfirmed by the facts are given lower weight, as model plausibility measures, in the Bayesian model comparison and averaging framework adopted. In this way a plurality of arguments is allowed yet a single judgement based on all arguments is possible and rational. (shrink)

The use of MABS (Multi-Agent Based Simulations) is analysed as the modelling of distributed (usually social) systems using MAS as the model structure. It is argued that rarely is direct modelling of target systems attempted but rather an abstraction of the target systems is modelled and insights gained about the abstraction then applied back to the target systems. The MABS modelling process is divided into six steps: abstraction, design, inference, analysis, interpretation and application. Some types of MABS papers are (...) characterised in terms of the steps they focus on and some criteria for good MABS formulated in terms of the soundness with which the steps are established. Finally some practical proposals that might improve the informativeness of the field are suggested. (shrink)

Quantum cognition research applies abstract, mathematical principles of quantum theory to inquiries in cognitive science. It differs fundamentally from alternative speculations about quantum brain processes. This topic presents new developments within this research program. In the introduction to this topic, we try to answer three questions: Why apply quantum concepts to human cognition? How is quantum cognitive modeling different from traditional cognitive modeling? What cognitive processes have been modeled using a quantum account? In addition, a brief introduction to quantum probability (...) theory and a concrete example is provided to illustrate how a quantum cognitive model can be developed to explain paradoxical empirical findings in psychological literature. (shrink)

A two-systems model of moral judgment proposed by Joshua Greene holds that deontological moral judgments (those based on simple rules concerning action) are often primary and intuitive, and these intuitive judgments must be overridden by reflection in order to yield utilitarian (consequence-based) responses. For example, one dilemma asks whether it is right to push a man onto a track in order to stop a trolley that is heading for five others. Those who favor pushing, the utilitarian response, usually take (...) longer to respond than those who oppose pushing. Greene's model assumes an asymmetry between the processes leading to different responses. We consider an alternative model based on the assumption of symmetric conflict between two response tendencies. By this model, moral dilemmas differ in the "difficulty" of giving a utilitarian response and subjects differ in the "ability" (tendency) to give such responses. (We could just as easily define ability in terms of deontological responses, as the model treats the responses symmetrically.) We thus make an analogy between moral dilemmas and tests of cognitive ability, and we apply the Rasch model, developed for the latter, to estimate the ability-difficulty difference for each dilemma for each subject. We apply this approach to five data sets collected for other purposes by three of the co-authors. Response time (RT), including yes and no responses, is longest when difficulty and ability match, because the subject is indifferent between the two responses, which also have the same RT at this point. When we consider yes/no responses, RT is longest when the model predicts that the response is improbable. Subjects with low ability take longer on the "easier" dilemmas, and vice versa. (shrink)

one takes to be the most salient, any pair could be judged more similar to each other than to the third. Goodman uses this second problem to showthat there can be no context-free similarity metric, either in the trivial case or in a scientifically ...

Although some previous studies have investigated the relationship between moral foundations and moral judgment development, the methods used have not been able to fully explore the relationship. In the present study, we used Bayesian Model Averaging (BMA) in order to address the limitations in traditional regression methods that have been used previously. Results showed consistency with previous findings that binding foundations are negatively correlated with post-conventional moral reasoning and positively correlated with maintaining norms and personal interest schemas. In addition (...) to previous studies, our results showed a positive correlation for individualizing foundations and post-conventional moral reasoning. Implications are discussed as well as a detailed explanation of the novel BMA method in order to allow others in the field of moral education to be able to use it in their own studies. (shrink)

In this paper, we explore the conceptual problems arising when using network analysis in person- centered care (PCC) in psychiatry. Personalized network models are potentially helpful tools for PCC, but we argue that using them in psychiatric practice raises boundary problems, i.e., problems in demarcating what should and should not be included in the model, which may limit their ability to provide clinically-relevant knowledge. Models can have explanatory and representational boundaries, among others. We argue that we can make more (...) explicit what kind of questions personalized network models can address in PCC, given their representational and explanatory boundaries, using perspectival reasoning. (shrink)

ABSTRACT School psychologists are frequently confronted with ethically challenging situations arising from the need to balance multiple parties’ competing interests and the challenge of serving as both student advocate and school employee. Use of a systematic decision-making model has been recommended as a way of improving the quality of school psychologists’ ethical decisions. In the present study, school psychology practitioners were randomly assigned to one of two conditions: a Critical Evaluative condition, requiring the use of a problem-solving approach to (...) resolve an ethical dilemma, or an Intuitive condition, which entailed generating a solution based solely on intuition and professional experience/judgment. Use of a formal decision-making model did not result in higher caliber ethical resolutions. Participants’ age and number of years in the field were significantly correlated with raters’ judgments that solutions considered the consequences of a chosen course of action. Most participants reported that they did not utilize an ethical decision-making model during the course of their practice, relying instead on consultation with peers/colleagues and their own professional experience. Implications of these findings are discussed in the context of school psychology practice. (shrink)