Beyond Particular Problem Instances: How to Create Meaningful and Generalizable Results

Computational intelligence methods have gained importance in several real-world domains such as process optimization, system identification, data mining, or statistical quality control. Tools are missing, which determine the applicability of computational intelligence methods in these application domains in an objective manner. Statistics provide methods for comparing algorithms on certain data sets. In the past, several test suites were presented and considered as state of the art. However, there are several drawbacks of these test suites, namely: (i) problem instances are somehow artificial and have no direct link to real-world settings; (ii) since there is a fixed number of test instances, algorithms can be fitted or tuned to this specific and very limited set of test functions; (iii) statistical tools for comparisons of several algorithms on several test problem instances are relatively complex and not easily to analyze. We propose a methodology to overcome these difficulties. It is based on standard ideas from statistics: analysis of variance and its extension to mixed models. This paper combines essential ideas from two approaches: problem generation and statistical analysis of computer experiments

Can You Provide the Current Trends in HR on People Analytics?

[Excerpt] People analytics is an increasingly hot topic and many companies are working to gain insight through this emerging field. Business leaders are asking how analytics can help drive better decision-making in order to improve business results. Among these questions, turnover prediction and succession planning are two key areas that HR professionals identify as high value. Since there isn’t a one-size- fits-all solution to these questions, we compiled our most noteworthy insights and put forward several steps that an organization should follow in order to create its own internal models

Can We Build Behavioral Game Theory?

The way economists and other social scientists model how people make interdependent decisions is through the theory of games. Psychologists and behavioral economists, however, have established many deviations from the predictions of game theory. In response to these findings, a broad movement has arisen to salvage the core of game theory. Extant models of interdependent decision-making try to improve their explanatory domain by adding some corrective terms or limits. We will make the argument that this approach is misguided. For this approach to work, the deviations would have to be consistent. Drawing in part on our experimental results, we will argue that deviations from classical models are not consistent for any individual from one task to the next or between individuals for the same task. In turn, the problem of finding an equilibrium strategy is not easier but rather is exponentially more difficult. It does not seem that game theory can be repaired by adding corrective terms (such as consideration of personal characteristics, social norms, heuristic or bias terms, or cognitive limits on choice and learning). In what follows, we describe new methods for investigating interdependent decision-making. Our experimental results show that people do not choose consistently, do not hold consistent beliefs, and do not in general align actions and beliefs. We will show that experimental choices are inconsistent in ways that prevent us from drawing general characterizations of an individual’s choices or beliefs or of the general population\u27s choices and beliefs. A general behavioral game theory seems a distant and, at present, unfulfilled hope

Research versus practice in quality improvement? Understanding how we can bridge the gap

The gap between implementers and researchers of quality improvement (QI) has hampered the degree and speed of change needed to reduce avoidable suffering and harm in health care. Underlying causes of this gap include differences in goals and incentives, preferred methodologies, level and types of evidence prioritized and targeted audiences. The Salzburg Global Seminar on 'Better Health Care: How do we learn about improvement?' brought together researchers, policy makers, funders, implementers, evaluators from low-, middle- and high-income countries to explore how to increase the impact of QI. In this paper, we describe some of the reasons for this gap and offer suggestions to better bridge the chasm between researchers and implementers. Effectively bridging this gap can increase the generalizability of QI interventions, accelerate the spread of effective approaches while also strengthening the local work of implementers. Increasing the effectiveness of research and work in the field will support the knowledge translation needed to achieve quality Universal Health Coverage and the Sustainable Development Goals.Fil: Hirschhorn, Lisa R.. Northwestern University; Estados UnidosFil: Ramaswamy, Rohit. University of North Carolina; Estados UnidosFil: Devnani, Mahesh. Post Graduate Institute of Medical Education & Research; IndiaFil: Wandersman, Abraham. University Of South Carolina; Estados UnidosFil: Simpson, Lisa A.. Academy Health; Estados UnidosFil: Garcia Elorrio, Ezequiel. Consejo Nacional de Investigaciones Científicas y Técnicas; Argentina. Instituto de Efectividad Clínica y Sanitaria; Argentin

A posteriori agreement as a quality measure for readability prediction systems

All readability research is ultimately concerned with the research question whether it is possible for a prediction system to automatically determine the level of readability of an unseen text. A significant problem for such a system is that readability might depend in part on the reader. If different readers assess the readability of texts in fundamentally different ways, there is insufficient a priori agreement to justify the correctness of a readability prediction system based on the texts assessed by those readers. We built a data set of readability assessments by expert readers. We clustered the experts into groups with greater a priori agreement and then measured for each group whether classifiers trained only on data from this group exhibited a classification bias. As this was found to be the case, the classification mechanism cannot be unproblematically generalized to a different user group

Islam: región MENA y métodos de investigación

The distinction between normative and objective knowledge and how social scientist imagine that their research is solely built on objectivity is currently being challenged especially in the political science field. If we take culture as an example and more specifically the question of identity and identity politics in the Middle East, we will find that the current modus operandi in political science research is distancing itself from objective knowledge because of the increased focus in the field on quantification. Whether one analyzes the work of Telhami on Identity in the Middle East, or Lynch’s “The Arab Uprisings Explained”, one will find that they all reflect on the academic conundrum that the field is facing.La distinción entre el conocimiento normativo y el conocimiento objetivo, así como el modo en que los científicos sociales imaginan su investigación en términos o no de objetividad, es algo que viene discutiéndose actualmente, especialmente en el campo de la ciencia política. Considerando la cultura y, más específicamente, la cuestión de la identidad y las políticas de identidad en Oriente Medio, encontramos que el modus operandi actual en la investigación de la ciencia política se está alejando del conocimiento objetivo debido al mayor enfoque en el campo de la cuantificación. Si uno analiza el trabajo de Telhami sobre Identidad en Oriente Medio, o bien las razones de los llamados “levantamientos” árabes de Lynch, encontrará que todos ellos cuestionan el rango académico del campo de estudio

Moving Toward a Culture of Evidence: Documentation and Action Research inside CAPE Veteran Partnerships

This report is a culmination of three years of study of the impact on effective teaching of educators and artists engaging as partners in action research (inquiry based study of their own practice), in documenting the effects of arts integration on student learning (creating a "culture of evidence"), and in collaborating with other action research teams and with formal researchers to actively investigate qualities of teaching and learning at participating schools (what CAPE calls "layered research")

Decision-making and strategic thinking through analogies

When faced with a complex scenario, how does understanding arise in one’s mind? How does one integrate disparate cues into a global, meaningful whole? Consider the chess game: how do humans avoid the combinatorial explosion? How are abstract ideas represented? The purpose of this paper is to propose a new computational model of human chess intuition and intelligence. We suggest that analogies and abstract roles are crucial to solving these landmark problems. We present a proof-of-concept model, in the form of a computational architecture, which may be able to account for many crucial aspects of human intuition, such as (i) concentration of attention to relevant aspects, (ii) \ud how humans may avoid the combinatorial explosion, (iii) perception of similarity at a strategic level, and (iv) a state of meaningful anticipation over how a global scenario \ud may evolve

A Personal Perspective on Daily Occupations to Counteract Cancer Related Fatigue: A Case Study

Background: This case study aimed to identify and describe meaningful physical occupations used by a cancer survivor to increase or maintain levels of participation during active chemotherapy and subsequent cancer related fatigue. Method: A case study approach was used to develop an in-depth description and analysis based on one participant’s experience with breast cancer and associated treatments. A semi-structured interview was conducted. The data were analyzed through description of the case, categories, and themes. It also included categorical aggregation in efforts to seek a collection of instances from the data to explore any issue-relevant meanings. Results: Following data analysis, one overarching theme, return to normalcy, was identified with three subthemes: (a) prioritization of meaningful activities, (b) modifications to activities or routines, (c) lack of referral for immediate needs. Conclusion: Personal knowledge of occupational therapy practice provided support for enhancing engagement in daily meaningful occupations. Lessons learned from this experience could be applied to clients experiencing cancer related side effects to improve engagement in daily occupations