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Any topic can be sensitive, and every subject area will have sensitive issues and topics that academics in higher education and further education settings will be expected to negotiate. Your ability to negotiate sensitive topics is important because the ways in which you engage and teach about sensitive topics will affect your ability to provide a positive learning experience and teaching alliance with students. In practice, you will face enormous pressure to ‘deliver’ on teaching, which will only be mirrored by similar freedoms in deciding on how and what needs to be done to get students to where they need to be. Negotiating, identifying, preparing for and delivering teaching on sensitive subjects and topics can be difficult in individual academics. This chapter, seeks to prepare you for developing a deeper understanding of some of the philosophical, theoretical, and practical-based concerns and issues related to teaching sensitive topics and subjects. This chapter begins with providing a rationale for what follows, and it explores some of the key themes, positionality, identity, transformational learning and lived experience, that are explored in greater depth in the collection. This chapter also contains a detailed breakdown of the structure and the content of this edited collection, and it concludes with some reflective comments about the implications of the collection for you as an individual and your career.

Digital trace data provide new opportunities to study how individuals act and interact with others online. One advantage of this type of data is that it measures behavior in a less obtrusive way than surveys, potentially reducing measurement error. However, it is well documented that in observational studies, participants' awareness of being observed can change their behavior, especially when the behavior is considered sensitive. Very little is known regarding this effect in the online realm. Against this background, we studied whether people change their online behavior because digital trace data are being collected.

We analyzed data from a sample of 1,959 members of a German online panel who had consented to the collection of digital trace data about their online browsing and/or mobile app usage. To identify reactivity, we studied change over time in five types of sensitive online behavior.

We found that the frequency and duration with which individuals engage in sensitive behaviors online gradually increases during the first couple of days after the installation of a tracker, mainly individuals who extensively engage in sensitive behavior show this pattern of increase after installation and this change in behavior is limited to certain types of sensitive online behavior.

There is an increased interest in the use of digital trace data in the social sciences and our study is one of the first methodological contributions measuring reactivity in digital trace data measurement.

This study examines the effect of the environmental sensitivity of firms on the relationship between integrated reporting (IR) quality and sustainability performance. Prior research works focus on the nexus between IR quality and sustainability performance with little attention to factors that moderate this relationship.

Ordinary least squares (OLS) and other robust estimations are employed to analyse the data of firms on the Johannesburg Stock Exchange (JSE).

This study finds a positive association between IR quality and sustainability performance. However, the strength of this relationship is found to be weaker among environmentally sensitive firms, thereby raising concerns that such firms may be reporting less sustainability information with the mandatory implementation of IR on the JSE.

The findings highlight the need for regulatory bodies to consider additional sustainability disclosure requirements for firms in environmentally sensitive industries.

The findings should make regulatory bodies aware of the possible actions of environmentally sensitive firms in relation to sustainability information within a mandatory setting of IR.

The study extends the existing literature on IR and sustainability performance by considering the effect of firm environmental sensitivity as a moderating factor.

This paper aims to present new technological approaches of manufacturing of micromechanical gyroscope ring-sensitive element based on the nanoporous anodic alumina instead of traditional silicon technology. Simulation and the operation analyses of such elements have been performed.

The design of gyroscope represents a sensitive element on a glass substrate; in the center of a ring, there is a permanent magnet in a steel box. The sensitive element is made of profiled nanoporous anodic alumina consisting of an octagonal frame which is connected to a ring in the center with eight N-shaped spokes. The technology of the sensitive element fabrication involves the electrochemical formation of nanoporous anodic alumina substrate given the thickness and porosity and its chemical etching on the element topology. The basic parameters and the operation principle of the nanoporous alumina-sensitive element have been defined by finite element simulation.

It is shown that the resonance frequencies of the sensitive element change as functions of the alumina porosity. The main parameters of the nanoporous alumina-sensitive element have been compared with parameters of a silicon-sensitive element. Calculations have shown that the mechanical deformations of the von Mises are approximately lower by two times in the nanoporous alumina-sensitive element.

High-precision angular rate measurement will be achieved by reducing mechanical and electrical noises practically to zero through careful designing of a ring magnetoelectric gyroscope

The ring resonator made of nanoporous anodic alumina will allow to increase the threshold of sensitivity and stability of micromechanical gyroscope characteristics owing to the high precision of geometric dimensions, the stability of the elastic properties and the quality factor.

The literature relating to asking sensitive questions in surveys is reviewed and evaluated. It is argued that work relating to the nature of associated response effects and the development of strategies designed to cope with these embodies a number of largely unexamined assumptions. These are identified in three main areas. First, clarification is necessary in relation to the way in which sensitivity is defined and operationalised. Second, the relationship between sensitivity and context is explored with particular reference to identity. Finally, some of the implications of the link between assurances of anonymity and responses to sensitive questions are explored. In conclusion it is suggested that the benefits of methodology sophistication will be most apparent in the context of the theoretical development of these issues.

The purpose of this paper is to investigate the manufacturer’s production, pricing and green technology investment decision problem when strategic customer behavior and carbon emissions-sensitive random demand is taken into consideration and discuss the impact of carbon emissions-sensitive demand on the manufacturer’s operation strategies, total carbon emissions and maximum expected profit.

The authors formulate a model to introduce carbon emissions-sensitive demand into the newsvendor framework with strategic customer behavior. The authors characterize the rational expectations equilibrium to derive the optimal solutions to the manufacturer. The authors analyze the effects of carbon emissions-sensitive demand on the manufacturer’s optimal strategies, total carbon emissions and maximum expected profit by comparative analysis.

The authors obtain the manufacturer’s optimal production, pricing and green technology investment strategies under rational expectations equilibrium in scenario of price-sensitive demand and that of carbon emissions-sensitive demand, respectively. The authors find that as customer demand changes from price-sensitive demand to carbon emissions-sensitive demand, the manufacturer’s optimal prices are the same but optimal production quantity, optimal unit carbon emissions and maximum expected profit go down. Though the total emissions decrease, the carbon emissions reduction would not increase as the demand is more carbon emissions-sensitive. Whether it increases or decreases depends on the model parameters.

Carbon emissions-sensitive demand and strategic customer behavior are considered simultaneously in an integrated model. The result can guide the manufacturer decision-making. The proposed model are hoped to shed light to the future works in the field of sustainable supply chain management.

The purpose of this paper is to focus on the methodological challenges in the design and implementation of an emotionally sensitive topic involving research with adolescents based on a study evaluating the experiences of adolescents and families facing a diagnosis of maternal cancer.

This conceptual paper builds an argument based on experiences from the field of qualitative data collection with adolescents and builds on arguments that were identified in the literature to provide with a detailed argument on the methodological challenges that researchers can face while undertaking sensitive research with young people.

Carrying out research on sensitive topics is challenging because rigour can be affected by real people experiencing pain, sorrow and other emotions linked to sensitive and difficult moments in their lives. Researchers need to decide how they will deal with the emotional impact that these topics can have on them as people but also continue to carry out high quality research.

This paper adds to the current body of knowledge by describing the challenges faced in the field carrying out data on sensitive issues with adolescents but it also provides alternatives and solutions on how these limitations can be overcome from early stages of the research design until the dissemination of results.

This paper aims to investigate three different orientations of recruitment (profession-sensitive, language-sensitive and interculture-sensitive recruitment) and their effect on the foreign subsidiaries of multinational corporations (MNCs).

This study examines the relationship among three different orientations of recruitment and knowledge transfer from parent firms to foreign subsidiaries. Data are collected from local managers in MNCs’ subsidiaries operating in Japan using a questionnaire. The hypotheses are tested by using ordinary least squares resression (OLS).

The results of this study indicate that each of the three orientations of recruitment positively influences the knowledge transfer of MNCs. In particular, the positive effect of profession-sensitive recruitment is enhanced when foreign subsidiaries are established through acquisition. The positive effect of interculture-sensitive recruitment on knowledge transfer is also strengthened by offering professional training.

This study is subject to several limitations. The sample size is small, and the data were collected from a single country. In addition, the respondents’ positions in an organizational hierarchy have not been taken into account. Despite these limitations, this study can be considered the first step toward future research on the relationship between different orientations of recruitment and intra-organizational knowledge transfer.

The results of this study indicate that not only profession-sensitive recruitment but also language-sensitive and interculture-sensitive recruitment are important for intra-organizational knowledge sharing. This study suggests that local employees with intercultural competence have the potential to improve subsidiary performance through knowledge sharing with parent firms if they are provided with professional training.

This study has empirically examined the complex mechanism of the three important factors (professional, language and intercultural competence) in recruitment and their influence on knowledge transfer. In particular, this study emphasizes language-sensitive recruitment and interculture-sensitive recruitment, which have received less attention than profession-sensitive recruitment in international business research. Moreover, this study focuses on the relationship between recruitment and knowledge sharing in a cross-border setting, which few studies in the human resource management area have examined.

This paper aims to describe the use of a meta-learning framework for recommending cost-sensitive classification methods with the aim of answering an important question that arises in machine learning, namely, “Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem?”

This paper describes the use of a meta-learning framework for recommending cost-sensitive classification methods for the aim of answering an important question that arises in machine learning, namely, “Among all the available classification algorithms, and in considering a specific type of data and cost, which is the best algorithm for my problem?” The framework is based on the idea of applying machine learning techniques to discover knowledge about the performance of different machine learning algorithms. It includes components that repeatedly apply different classification methods on data sets and measures their performance. The characteristics of the data sets, combined with the algorithms and the performance provide the training examples. A decision tree algorithm is applied to the training examples to induce the knowledge, which can then be used to recommend algorithms for new data sets. The paper makes a contribution to both meta-learning and cost-sensitive machine learning approaches. Those both fields are not new, however, building a recommender that recommends the optimal case-sensitive approach for a given data problem is the contribution. The proposed solution is implemented in WEKA and evaluated by applying it on different data sets and comparing the results with existing studies available in the literature. The results show that a developed meta-learning solution produces better results than METAL, a well-known meta-learning system. The developed solution takes the misclassification cost into consideration during the learning process, which is not available in the compared project.

The proposed solution is implemented in WEKA and evaluated by applying it to different data sets and comparing the results with existing studies available in the literature. The results show that a developed meta-learning solution produces better results than METAL, a well-known meta-learning system.

The paper presents a major piece of new information in writing for the first time. Meta-learning work has been done before but this paper presents a new meta-learning framework that is costs sensitive.

The study aims to identify the impact of board characteristics (BC) on a firm's environmental performance, and provides future research directions in the area of BC impact on environmental disclosures (ED) in case of India's environmentally sensitive and non-sensitive industries (SI and NSI).

The authors collect firm-level data from Prowess and Bloomberg, which cover 1,158 firm-year observations from National Stock Exchange of India (NSE) 500 listed companies from 2015 to 2020, and use a dynamic panel regression analysis to get deeper insights on the relationship of ED and BC.

The study found that lagged environment disclosure score is positively and significantly associated with current environmental disclosure scores. The presence of sustainability committee, board size and frequency of meetings has a positive and significant association with ED for sensitive as well as non-sensitive industry groups. Factors such as board Independence, board gender diversity and CEO duality have no significant impact on ED of both sensitive and non-sensitive industry groups.

Based on agency theory and stakeholder theory authors study for the first time in the context of India the effect of BC on ED using a large sample and covering an extensive period of six years. This study contributes by offering deep insights about the impact in case of “environmentally sensitive, non-sensitive and also all industries case”. The findings of this study are valuable for corporate managers and regulators who are interested in improving ED practices through a better-governed corporate mechanism.