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The purpose of this study is to develop a method to assess social performance. Traditionally, environment, social and governance (ESG) rating providers use subjectively weighted arithmetic averages to combine a set of social performance (SP) indicators into one single rating. To overcome this problem, this study investigates the preconditions for a new methodology for rating the SP component of the ESG by applying machine learning (ML) and artificial intelligence (AI) anchored to social controversies.

This study proposes the use of a data-driven rating methodology that derives the relative importance of SP features from their contribution to the prediction of social controversies. The authors use the proposed methodology to solve the weighting problem with overall ESG ratings and further investigate whether prediction is possible.

The authors find that ML models are able to predict controversies with high predictive performance and validity. The findings indicate that the weighting problem with the ESG ratings can be addressed with a data-driven approach. The decisive prerequisite, however, for the proposed rating methodology is that social controversies are predicted by a broad set of SP indicators. The results also suggest that predictively valid ratings can be developed with this ML-based AI method.

This study offers practical solutions to ESG rating problems that have implications for investors, ESG raters and socially responsible investments.

The proposed ML-based AI method can help to achieve better ESG ratings, which will in turn help to improve SP, which has implications for organizations and societies through sustainable development.

To the best of the authors’ knowledge, this research is one of the first studies that offers a unique method to address the ESG rating problem and improve sustainability by focusing on SP indicators.

In this chapter, we focus on specially designed instruction (SDI) as a core value for the field of specific learning disabilities (SLD). SDI is at the heart of special education, and the field of LD has been built on the core value that effective instruction improves student outcomes. We describe a two-step test and an extended example of what is and is not SDI for Matt, a student with an SLD. Finally, we discuss some of the confusion surrounding SDI and the need for the field to return to its core value of individualized, intentional, targeted, evidence- or high leverage practice–based, and systematic instruction for students with SLD.

This chapter is structured for teaching young learners with other health impairments in special education. Under the Individuals with Disabilities Education Improvement Act (IDEA, 2004), other health impairments represent chronic or acute health problems such as asthma, attention deficit disorder or attention deficit hyperactivity disorder (ADHD), diabetes, epilepsy, a heart condition, hemophilia, lead poisoning, leukemia, nephritis, rheumatic fever, and sickle cell anemia and adversely affect a child’s educational performance. The chapter is organized around definitions, prevalence, etiologies, intervention strategies, and teaching considerations for selected disabling conditions in this disability category.

The purpose of this paper is to study how the concept “middle archive” is related to the Swedish archival theory and practice, by exploring its background and its practical and theoretical implications. The overarching aim is to increase the understanding of the interrelations between the archival theory and practice, with a special focus on changes occurring in the digital environment in Sweden.

The paper is based on a qualitative study of texts produced between 2010 and 2013, which were read and analyzed iteratively. The research design and analysis is inspired by Dryden (2014) who recommends taking the context into account. The three types of digital repository developed by Millar (2010) are used as a comparison to further extend the understanding of the concept of the “middle archive”.

The findings indicate that the “middle archive” was introduced as a solution to practical problems of managing digital records, and that there is a need to further discuss how the term relates to existing theoretical, legal and administrative contexts.

The study is limited to contemporary Sweden. The researcher did not follow the discussions and drafts which contributed to the development of the final definitions of the “middle archive”.

The study contributes to the research and development of archival concepts, with a special focus on recent developments in Sweden. The paper highlights some of the challenges relating to archives and records in the context of e- government development.

This paper gives a bibliographical review of the finite element and boundary element parallel processing techniques from the theoretical and application points of view. Topics include: theory – domain decomposition/partitioning, load balancing, parallel solvers/algorithms, parallel mesh generation, adaptive methods, and visualization/graphics; applications – structural mechanics problems, dynamic problems, material/geometrical non‐linear problems, contact problems, fracture mechanics, field problems, coupled problems, sensitivity and optimization, and other problems; hardware and software environments – hardware environments, programming techniques, and software development and presentations. The bibliography at the end of this paper contains 850 references to papers, conference proceedings and theses/dissertations dealing with presented subjects that were published between 1996 and 2002.

We analyze the correlation between the political orientation of investors and their financial risk tolerance. Assessing financial risk tolerance is a very important aspect to developing an appropriate long‐term investing strategy. Our study is based on a sample of 129 undergraduates at Central Michigan University during one academic year. We employ a two‐axis political compass to determine the political orientation of our study participants. We determine their financial risk tolerance by analyzing their portfolios and trading behavior in a simulated investment game in a semester long course. We report two main findings: (1) financial risk tolerance is highest for those with more conservative economic political views and (2) financial risk tolerance is highest for those with more centrist social political views. We believe our results can help investment advisors and individual investors better assess individual financial risk tolerance through the use of the two‐axis political compass utilized in our study.

The study aims to present a logic map linking the Professional Development School (PDS) Nine Essentials as a PDS theory of action and offer an analysis of dissertations that compare outcomes of learning in PDS and non-PDS contexts.

For this current study, the authors identified 25 of the 210 dissertations from a larger study that used a comparison methodology to provide a window into how learning in PDS and non-PDS settings may differ. In reviewing these comparison studies, the authors identified a set of clustered themes, as well as a variety of comparison constructs and measurements researchers used to determine the impact of PDS.

Five themes emerged including (1) the experience of learning to teach in a PDS setting vs. a non-PDS; (2) the experience of teaching in a PDS vs. non-PDS; (3) teacher candidate quality in a PDS vs. non-PDS; (4) teacher quality in a PDS vs. non-PDS; (5) school leader quality in a PDS vs. non-PDS; and (6) K-12 student learning in PDS vs. non-PDS.

Limitations of this study include the complications related to comparison, logic-related fallacies and the complexity of capturing simultaneous renewal.

In the 30th year of PDS work, the study utilizes a theory of action comprised of linking the PDS Nine Essentials to situate the comparison dissertation analysis of outcomes in PDS and non-PDS contexts suggesting challenges and possibilities and perhaps a direction for new research questions.

The purpose of this paper is to describe the most important areas of maintenance management system for heavy industries for helping maintenance mangers to focus on measuring the effectiveness of maintenance system. This work aimed at inferring relationships between maintenance management, maintenance practices and maintenance improvement.

In relation to maintenance management, as a case study approach, it can be applied to continuous improvement maintenance systems through 15 maintenance process areas.

The general picture evidences some criticalities, such as those areas which help in the success of maintenance management and areas which lead to the failure of maintenance management. It was found that by using the maintenance management system in the cement industry, it was possible to measure and improve about 15 percent maintenance performance which can be achieved by enhancing maintenance in the suggested areas.

Continuous maintenance improvement (CMI) is an ongoing effort to improve maintenance aimed at maintenance process simplification and reduction or elimination of maintenance process waste. To support CMI, maintenance engineers continually examine maintenance processes to discover and eliminate problems.

Other researchers have reported on the maintenance management system, but most of them have focussed on limited areas. The lack of useful and practical research has been determined. It seems that the scientific knowledge of maintenance management still needs more effort. This study is one of the first in-depth studies into actual condition-based maintenance practice to test 15 maintenance process areas.

In this paper, the authors use a new methodology, called paper affiliation index, to create finance journal ranking using expert judgment and research impact, both of which are based on secondary, objective measures, thus making it possible to produce lists every year without human manipulation at virtually no cost.

Bibliometrics. Python implementation.

A new ranking with 65 finance journals.

This procedure helps to reduce bias and to deal with known problems associated with current methodologies. The data used in the methodology comes from public sources; the procedure is therefore easily replicable. This methodology is not subject-dependent and thus can be transferred to other realms of knowledge. Once the bibliometric institutional data has been gathered, the procedure is not computationally costly: a Python implementation of the algorithm executes the whole computation in a few seconds. Results seem to correct the pernicious Matthew effect which is so evident in citation-based methods.

The institutional classification created includes all institutions that have contributed papers to the field of finance. The procedure helps to reduce bias and to deal with known problems associated with current methodologies. The data used in the methodology comes from public sources, the procedure is therefore easily replicable. The methodology is not subject-dependent and thus can be transferred to other realms of knowledge. Once the bibliometric institutional data has been gathered, the procedure is not computationally costly.