Our beliefs and opinions are shaped by others, making our social networks crucial in determining what we believe to be true. Sometimes this is for the good because our peers help us form a more accurate opinion. Sometimes it is for the worse because we are led astray. In this context, we address via agent-based computer simulations the extent to which patterns of connectivity within our social networks affect the likelihood that initially undecided agents in a network converge on a (...) true opinion following group deliberation. The model incorporates a fine-grained and realistic representation of belief and trust, and it allows agents to consult outside information sources. We study a wide range of network structures and provide a detailed statistical analysis concerning the exact contribution of various network metrics to collective competence. Our results highlight and explain the collective risks involved in an overly networked or partitioned society. Specifically, we find that 96% of the variation in collective competence across networks can be attributed to differences in amount of connectivity and clustering, which are negatively correlated with collective competence. A study of bandwagon or “group think” effects indicates that both connectivity and clustering increase the probability that the network, wholly or partly, locks into a false opinion. Our work is interestingly related to Gerhard Schurz’s work on meta-induction and can be seen as broadly addressing a practical limitation of his approach. (shrink)

Forensic evidence often involves an evaluation of whether two impressions were made by the same source, such as whether a fingerprint from a crime scene has detail in agreement with an impression taken from a suspect. Human experts currently outperform computer-based comparison systems, but the strength of the evidence exemplified by the observed detail in agreement must be evaluated against the possibility that some other individual may have created the crime scene impression. Therefore, the strongest evidence comes from features in (...) agreement that are also not shared with other impressions from other individuals. We characterize the nature of human expertise by applying two extant metrics to the images used in a fingerprint recognition task and use eye gaze data from experts to both tune and validate the models. The Attention via Information Maximization model quantifies the rarity of regions in the fingerprints to determine diagnosticity for purposes of excluding alternative sources. The CoVar model captures relationships between low-level features, mimicking properties of the early visual system. Both models produced classification and generalization performance in the 75%–80% range when classifying where experts tend to look. A validation study using regions identified by the AIM model as diagnostic demonstrates that human experts perform better when given regions of high diagnosticity. The computational nature of the metrics may help guard against wrongful convictions, as well as provide a quantitative measure of the strength of evidence in casework. (shrink)

We argue that inductive analysis and operational assessment of the scientific process can be justifiably and fruitfully brought together, whereby the citation metrics used in the operational analysis can effectively track the inductive dynamics and measure the research efficiency. We specify the conditions for the use of such inductive streamlining, demonstrate it in the cases of high energy physics experimentation and phylogenetic research, and propose a test of the method’s applicability.

Different proprietary databases have been used extensively in research to assess the environmental performance and environmental risk of companies. This study explores the convergent validity of the environmental ratings of MSCI ESG STATS, Thomson Reuters ASSET4 and Global Engagement Services. The study shows that the ratings have common dimensions, but on aggregate, they do not converge. On the environmental opportunity side, KLD environmental strengths, and ASSET4 and GES environmental performance metrics correlate highly and provide convergent scores for (...) US companies from 2003–2011. On the environmental risk side, KLD environmental concerns converge with the GES environmental industry risk and company emissions from the ASSET4 database. Further analysis confirms that industry-related risks are drivers of company-specific environmental performance. (shrink)

This article contributes to a growing conversation about the role of numbers in promoting gendered agendas in potentially contradictory ways. Drawing from interviews with gender advisors—the professionals tasked with mainstreaming gender in development projects—in an East African country, I begin from the paradox that gender advisors articulate a strong preference for qualitative data to best capture the lives of the women they aim to assist while voicing a need for quantitative metrics. I demonstrate that gender advisors come to imagine (...) metrics as expeditious bureaucratic tools able to inspire cooperation from otherwise reluctant coworkers. I argue that development organizations are gendered in ways—acutely seen in how advisors struggle, are sidelined, and attempt to advance their goals with numbers—that lead to the utility of valuing quantitative metrics over qualitative ones. I establish two theoretical contributions: Gendered organizations theory is essential to understanding the adoption and globalization of performance metrics, and in an age of evidence-based decision making, the utility of quantified data to garner resources is heightened, rewarding those who adopt quantified knowledge production. I coin the term “the paradox of quantified utility” to describe how these material advantages encourage even skeptics to value quantitative metrics. (shrink)

Les tests d’imagerie diagnostique médicale qui produisent des rayonnements ionisants utilisent désormais une technologie qui permet de connaître la dose de rayonnement cumulée d’un patient. Cela soulève la question de savoir s’il est impératif que les autorités sanitaires régionales divulguent ces informations aux médecins, qui peuvent alors faire participer leurs patients à la décision de savoir si les inconvénients potentiels valent les avantages de l’imagerie diagnostique ultérieure. Actuellement, les organismes professionnels qui fournissent des normes de pratique pour l’imagerie diagnostique médicale (...) conseillent de ne pas divulguer ces informations aux médecins. Ils craignent que les informations sur les doses cumulées soient difficiles à évaluer en termes de risque pour les patients individuels, qu’elles ne soient pas facilement applicables à la prise de décision clinique sur l’opportunité d’un examen d’imagerie ultérieur, et que les cliniciens référents se sentent obligés de proposer à un patient un test non ionisant moins efficace, ce qui pourrait avoir un impact négatif sur les soins prodigués au patient. Nous présentons une analyse critique de plusieurs hypothèses qui sous-tendent la position de non-divulgation. Travaillant à l’intersection de la physique médicale, de l’anthropologie médicale et de l’éthique clinique, nous proposons une autre formulation du discours sur le risque qui a façonné le récent débat scientifique sur la divulgation de la dose de rayonnement cumulée individuelle. Nous postulons qu’il est possible de présenter un argument convaincant contre la position des organismes professionnels et en faveur d’une politique de divulgation – à condition qu’une telle politique donne la priorité à la décision partagée centrée sur le patient. (shrink)

Data and metrics play an unmistakably powerful role in today's society. Over the years, their use has expanded to cover almost every sphere of everyday life. This book provides a critical investigation into what we can call a ""metric culture"" in which practices of self-tracking and quantification have become more popular than ever before.

In this paper, we propose an adaptive Gaussian incremental expectation stadium parameter estimation algorithm for sports video analysis and prediction through the study and analysis of sports videos. The features with more discriminative power are selected from the set of positive and negative templates using a feature selection mechanism, and a sparse discriminative model is constructed by combining a confidence value metric strategy. The sparse generative model is constructed by combining L1 regularization and subspace representation, which retains sufficient representational power (...) while dealing with outliers. To overcome the shortcomings of the traditional multiplicative fusion mechanism, this paper proposes an adaptive selection mechanism based on Euclidean distance, which aims to detect deteriorating models in time during the dynamic tracking process and adopt corresponding strategies to construct more reasonable likelihood functions. Based on the Bayesian citation framework, the adaptive selection mechanism is used to combine the sparse discriminative model and the sparse generative model. Also, different online updating strategies are adopted for the template set and Principal Component Analysis subspace to alleviate the drift problem while ensuring that the algorithm can adapt to the changes of target appearance in the dynamic tracking environment. Through quantitative and qualitative evaluation of the experimental results, it is verified that the algorithm proposed in this paper has stronger robustness compared with other classical algorithms. Our proposed visual object tracking algorithm not only outperforms existing visual object tracking algorithms in terms of accuracy, success rate, accuracy, and robustness but also achieve the performance required for real-time tracking in terms of execution speed on the central processing unit. This paper provides an in-depth analysis and discussion of the adaptive Gaussian incremental expectation stadium parameter estimation algorithm for sports video analysis. Using a variety of county-level algorithms for analysis and multiple solutions to improve the accuracy of the results, we obtain a more efficient and accurate algorithm. (shrink)

We address how listeners perceive temporal regularity in music performances, which are rich in temporal irregularities. A computational model is described in which a small system of internal self‐sustained oscillations, operating at different periods with specific phase and period relations, entrains to the rhythms of music performances. Based on temporal expectancies embodied by the oscillations, the model predicts the categorization of temporally changing event intervals into discrete metrical categories, as well as the perceptual salience of deviations from these categories. The (...) model's predictions are tested in two experiments using piano performances of the same music with different phrase structure interpretations (Experiment 1) or different melodic interpretations (Experiment 2). The model successfully tracked temporal regularity amidst the temporal fluctuations found in the performances. The model's sensitivity to performed deviations from its temporal expectations compared favorably with the performers' structural (phrasal and melodic) intentions. Furthermore, the model tracked normal performances (with increased temporal variability) better than performances in which temporal fluctuations associated with individual voices were removed (with decreased variability). The small, systematic temporal irregularities characteristic of human performances (chord asynchronies) improved tracking, but randomly generated temporal irregularities did not. These findings suggest that perception of temporal regularity in complex musical sequences is based on temporal expectancies that adapt in response to temporally fluctuating input. (shrink)

Machine learning, deep learning and neural networks are extensively applied for the development of many fields. Though their technologies are improved greatly, they are often said to be opaque in terms of explainability. Their explainable neural functions will be essential to realization in the networks. In this paper, it is shown that the bio-inspired networks are useful for the explanation of tracking and classification of features. First, the asymmetric network with nonlinear functions is created based on the bio-inspired retinal network. (...) They have orthogonal properties useful for the tracking of features compared with the conventional symmetric networks, which is also proposed on the biological functions. Next, the analysis for the independence of the subspaces between the Fourier bases and the asymmetric network bases is performed. It was that the asymmetric networks have better performances in the classification compared with the symmetric ones. Further, the layered asymmetric networks generate the higher dimensional orthogonal bases that improve the classification accuracies by the replacements of bases. Finally, we classified Reuters collections data applying the explainable processing steps, which consist of the linear discriminations and the sparse coding with nearest neighbor relation for classification. (shrink)

Despite the increasing importance of environmental, social and governance (ESG) factors, it is not fully understood whether companies consider these factors when designing compensation plans for their directors. This study investigated the extent to which directors’ remuneration integrates ESG factors. The study sample is made up of JSE-listed companies for the period 2015 to 2021. The estimated generalised least squares regression technique was used to analyse the data. The results show the shift towards the integration of ESG factors in directors’ (...) compensation plans. It should be established which ESG factors are pertinent in the South African context. (shrink)

Because ports are considered to be the heart of the maritime transportation system, thereby assessing port performance is necessary for a nation’s development and economic success. This study proposes a novel metric, namely, “_port performance index (PPI)_”, to determine the overall performance and utilization of inland waterway ports based on six criteria,_ port facility, port availability, port economics, port service, port connectivity, and port environment_. Unlike existing literature, which mainly ranks ports based on quantitative factors, this study (...) utilizes a Bayesian Network (BN) model that focuses on both quantitative and qualitative factors to rank a port. The assessment of inland waterway port performance is further analyzed based on different advanced techniques such as sensitivity analysis and belief propagation. Insights drawn from the study show that all the six criteria are necessary to predict PPI. The study also showed that port service has the highest impact while port economics has the lowest impact among the six criteria on PPI for inland waterway ports. (shrink)

In order to improve the accuracy and reliability of wireless location in NLOS environment, a wireless location algorithm based on artificial neural network is proposed for NLOS positioning error caused by non-line-of-sight propagation, such as occlusion and signal reflection. The mapping relationship between TOA and TDOA measurement data and coordinates is established. The connection weights of neural network are estimated as the state variables of nonlinear dynamic system. The multilayer perceptron network is trained by the real-time neural network training algorithm (...) based on extended Kalman. Combined with the statistical characteristics of NLOS error, the state component NLOS bias estimation is modified to realize TDOA data reconstruction. Simulation and experimental data analysis show that the algorithm can effectively weaken the influence of NLOS error. The localization method does not depend on the specific NLOS error distribution, nor does it need LOS and NLOS recognition. It can significantly improve the mobile positioning accuracy. (shrink)

This paper develops an adaptive fixed-time trajectory tracking controller of an underactuated hovercraft with a prescribed performance in the presence of model uncertainties and unknown time-varying environment disturbances. It is the first time that the proposed method is applied to the motion control of the hovercraft. To begin with, based on the hovercraft's four degrees of freedom model, the virtual control laws are designed using an error transforming function and the fixed-time stability theory to guarantee that the position tracking (...) errors are constrained within the prescribed convergence rates and minimum overshoot. In addition, by combining the Lyapunov direct method and the adaptive radial basis function neural network, the actual control laws are designed to ensure that the velocity tracking errors converge to a small region containing zero while handling model uncertainties and external disturbances effectively. Finally, all tracking errors of the closed-loop system are uniformly ultimately bounded and fixed-time convergent. Results from a comparative simulation study verify the effectiveness and advantage of the proposed method. (shrink)

This paper discusses the utilization of pilots' physiological indications such as electroencephalographic signals, ocular parameters, and pilot performance-based quantitative metrics to estimate cognitive workload. The study aims to derive a non-invasive technique to estimate pilot's cognitive workload and study their correlation with standard physiological parameters. Initially, we conducted a set of user trials using well-established psychometric tests for evaluating the effectiveness of pupil and gaze-based ocular metrics for estimating cognitive workload at different levels of task difficulty and (...) lighting conditions. Later, we conducted user trials with the NALSim flight simulator using a business class Learjet aircraft model. We analyzed participants' ocular parameters, power levels of different EEG frequency bands, and flight parameters for estimating variations in cognitive workload. Results indicate that introduction of secondary task increases pilot's cognitive workload significantly. The beta frequency band of EEG, nearest neighborhood index specifying distribution of gaze fixation, L1 Norm of power spectral density of pupil diameter, and the duty cycle metric indicated variations in cognitive workload. (shrink)

Individuals with high risk of internet gaming disorder showed abnormal psychological performances in response inhibition, impulse control, and emotion regulation, and are considered the high-risk stage of internet gaming disorder. The identification of this population mainly relies on clinical scales, which are less accurate. This study aimed to explore whether these performances have highly accurate for discriminating HIGD from low-risk ones. Eye tracking based anti-saccade task, Barratt impulsiveness scale, and Wong and Law emotional intelligence scale were used to evaluate psychological (...) performances in 57 individuals with HIGD and 52 matched low risk of internet gaming disorder. HIGD group showed significantly increased BIS total, attention, motor, and non-planning scores, but significantly decreased WLEIS emotion regulation score and correct rate of eye tracking anti-saccade task compared with LIGD group. BIS total score was negatively correlated with the WLEIS total and WLEIS emotion regulation scores. A combination of the WLEIS emotion regulation score and the correct rate of anti-saccade task could discriminate HIGD from LIGD with 91.23% sensitivity, 82.69% specificity, and 87.16% accuracy. Participants with higher gaming hours daily were 40 times more likely to be high risk than their counterparts. Hence, psychological performances were worse in HIGD. A combination of abnormal emotion regulation and response inhibition might be a potential marker to identify HIGD individuals. (shrink)

Three characteristic problems in the measurement of corporate social performance (CSP) center around the need to measure three “metrics”: the metric of performance evaluation (M1), the metric of performance measurement (M2), and the metric of performance perception and belief (M3). The central issues in each metric are commitment, revelation, and belief, respectively. This article discusses each metric and provides sets of theoretical propositions under M2 and M3 describing behavior in those contexts. Some of the propositions (...) inM2form an explicit partial theory of factors affecting the likelihood of CSP measurement. Those under M3 are developed from more general ones in the theory of testaments. (shrink)

This paper explores the circumstances that influence whether managers in the public services manipulate the measurement information that is used to assess performance; and if they do, what level of deception they might use. The realistic evaluation approach is adopted. A Delphi survey and the collection of critical incidents through interviews are used to identify possible configurations of contexts–mechanisms–outcomes that provide possible explanations of information manipulation. A number of these configurations are discussed. In a later stage of the project (...) these configurations will be further tested through another Delphi survey, with the intention of developing proposals for improved governance of performance measurement systems in the public services. (shrink)

Metrics shape our social worlds in many and more ways. Everyday quantifications of our preferences, our behaviors and our relationships, alter us and the institutions that we constitute. This essay takes a brief look at the metrics of business ethics through two analytic devices. Representation explains the notion that metrics can capture or demonstrate ethics and performativity explains the notion that metrics can shape or constitute ethics. The analytic distinction between representation and performativity is obscured in (...) practice when metrics become targets, indeed much of the social power of metrics comes from their use as targets. Hence, we should pay attention to the world of practice in which measuring and doing are entangled. However, we should not lose sight of the limitations of measurement and the possibility that there are areas of ethical life best left unmeasured. (shrink)

I argue that the work of art in rock music is a track constructed in the studio, that tracks usually manifest songs, which can be performed live, and that a cover version is a track (successfully) intended to manifest the same song as some other track. This ontology reflects the way informed audiences talk about rock. It recognizes not only the centrality of recorded tracks to the tradition, as discussed by Theodore Gracyk, but also the value accorded to live (...) class='Hi'>performance skills, emphasized by Stephen Davies. (shrink)

Most of us are familiar with the phenomenology of mental effort accompanying cognitively demanding tasks, like focusing on the next chess move or performing lengthy mental arithmetic. In this paper, I argue that phenomenology of mental effort poses a novel counterexample to tracking intentionalism, the view that phenomenal consciousness is a matter of tracking features of one’s environment in a certain way. I argue that an increase in the phenomenology of mental effort does not accompany a change in any of (...) the following candidate representational contents: representation of externally presented features, e.g. brightness, contrast, and so on representation of task difficulty, representation of the possibility of error, representation of trying to achieve some state of affairs, representation of bodily changes like muscle tension, or representation of change in cognitive resource availability and lost opportunity cost. While tracking intentionalism about some phenomenal experiences like pains might obtain, it does not seem to obtain for all phenomenal experiences. This puts the intentionalist into an uncomfortable position of trying to explain why some phenomenal experiences have representational content and not others. Since many believe that tracking intentionalism or something like it provides the best chance of naturalizing consciousness, these arguments deserve detailed consideration. (shrink)

Structure learning algorithms for graphical models have focused almost exclusively on stable environments in which the underlying generative process does not change; that is, they assume that the generating model is globally stationary. In real-world environments, however, such changes often occur without warning or signal. Real-world data often come from generating models that are only locally stationary. In this paper, we present LoSST, a novel, heuristic structure learning algorithm that tracks changes in graphical model structure or parameters in a dynamic, (...) real-time manner. We show by simulation that the algorithm performs comparably to batch-mode learning when the generating graphical structure is globally stationary, and significantly better when it is only locally stationary. (shrink)

Previous research on reactivity—defined as changing organizational behaviour to better conform to the criteria of measurement in response to being measured—has found significant variation in company responses toward sustainability metrics. We propose that reactivity is driven by dialogue, motivation, and capacity in a configurational way. Empirically, we use fuzzy set qualitative comparative analysis to analyze company responses to the sustainability index FTSE4Good. We find evidence of complementary and substitute effects between motivation and capacity. Based on these effects, we develop (...) a typology of reactivity to sustainability metrics, which also theorizes the use of metrics as tools for performance feedback and the building of calculative capacity. We show that when reactivity is studied configurationally, we can identify previously underacknowledged types of responses. We discuss the theoretical and practical implications for studying and using sustainability metrics as governance tools for responsible behaviour. (shrink)

In the mid twenty-tens, many major food companies committed to sustainably source their priority ingredients, including North American commodity crops. With deadlines set for the decade’s end, companies joined multi-stakeholder initiatives and developed standards, metrics, and other assessment tools to help them track and drive progress. In short, they embarked on the sort of corporate supply chain governance that agri-food scholars have long studied. But how would this governance happen, especially in the commodity supply chains where companies knew and (...) controlled little about upstream production? Treating supply chain governance as not just a corporate undertaking but also the work of mid-level sustainability managers, this paper examines the practical skills and knowledge, or mētis, employed by managers in their efforts to win the support of colleagues, farmers, and other supply chain actors. This analysis provides insight into how and why food companies’ approaches to governing agricultural sustainability have changed since they set their 2020 sourcing goals. More broadly, it highlights the contingent nature of their governance. (shrink)

In contrast to Constructivist Views, which construe perceptual cognition as an essentially reconstructive process, this article recommends the Deictic View, which grounds perception in perceptual-demonstrative reference and the use of deictic tracking strategies for acquiring and updating knowledge about individuals. The view raises the problem of how sensory-motor tracking connects to epistemic and integrated forms of tracking. To study the strategies used to solve this problem, we report a study of the ability to track distal individuals when only their directions (...) can be perceived and not their locations. We introduce a new experimental paradigm named the 'Modified Traveling Salesman Problem' (MTSP), which requires subjects to visit n invisible targets in a 2D display once each. Surprisingly, subjects are competent at this task for up to 10 targets. We consider two types of tracking strategies that subjects might use: 'location-based' strategies and 'deictic direction-based' strategies. A number of observations suggest that subjects used the latter, at least for larger numbers of targets. We hypothesize that subjects used perceptual-demonstrative reference and deictic strategies (i) to perform the sensory-motor tracking of directional segments, (ii) to bind the segments with their updated status in the task, and (iii) to perform the epistemic tracking of invisible targets by means of perception-based inferences. (shrink)