Knowledge constructions in research communities: The example of agri-rural researchers in Denmark

Construction of scientific knowledge can be seen as a struggle over who should define the terms and conditions of legitimate fields of research. Sociologists of scientific knowledge (SSK) have pointed to the importance of analysing scientific knowledge in the same way as other types of knowledge. This idea guides the present paper on Danish research in agriculture and rural areas. Based on an ethnographic study of researchers involved in rural studies, we take stock of the agri-rural research community in Denmark and reflect upon the how and why ‘fashions’ in Danish rural studies differ from ‘fashions’ in rural studies in the UK. In the analysis, we show how a research community construct and reconstruct itself in relation to what is perceived as legitimate fields of research. Finally, the paper gives insight into the research world of those doing research outside the UK and adds to the discussion of ‘putting philosophies of geography into practice’ that is on-going in British geography.     

The need for knowledge modification in technology change: a framework to consider changes in domain complexity,knowledge and productivity

This paper researches productivity in relation to domain complexity and the present knowledge capacity in an organisational context. The study is based on five very different case studies. Three studies are conducted in Denmark, Germany, Mexico and China and are related to knowledge transfer in the relocation of manufacturing facilities. Two studies investigate operation and automation of oil and gas production in the North Sea. The case study method involves semi-structured interviews, surveys, an analysis of historical production data and observations. Based on the findings from the field studies, the paper develops a conceptual framework that management can use for discussions of productivity, development of knowledge and design of learning programmes when considering changes in the complexity of a domain or a change in knowledge.     

Matched survival data in a co-twin control design

When using the co-twin control design for analysis of event times, one needs a model to address the possible within-pair association. One such model is the shared frailty model in which the random frailty variable creates the desired within-pair association. Standard inference for this model requires independence between the random effect and the covariates. We study how violations of this assumption affect inference for the regression coefficients and conclude that substantial bias may occur. We propose an alternative way of making inference for the regression parameters by using a fixed-effects models for survival in matched pairs. Fitting this model to data generated from the frailty model provides consistent and asymptotically normal estimates of regression coefficients, no matter whether the independence assumption is met.     

“Want to Stay Over?” Demographic,Intrapersonal, and Relational Differences Among Those Who Date,Stay-Over,and Cohabit

This study explored the potential uniqueness of staying over, or spending the night with a romantic partner, as a relationship status. Using a recent sample of 2,304 individuals in romantic relationships, we explored how staying over might be associated with demographic, intrapersonal, and relational characteristics. Results suggested that individuals in “stay-over relationships” were similar to those in dating relationships and that cohabiters, defined as those who lived with a romantic partner in the same residence, were the most likely to differ from those in other types of relationships on demographic, intrapersonal, and relational assessments. Staying over in the absence of cohabitation was not associated with differences in relationship outcomes once controls were taken into account, but cohabiters who were not spending the night together did report lower relationship satisfaction compared with cohabiters spending most nights together.     

Airline Safety Improvement Through Experience with Near‐Misses: A Cautionary Tale

In recent years, the U.S. commercial airline industry has achieved unprecedented levels of safety, with the statistical risk associated with U.S. commercial aviation falling to 0.003 fatalities per 100 million passengers. But decades of research on organizational learning show that success often breeds complacency and failure inspires improvement. With accidents as rare events, can the airline industry continue safety advancements? This question is complicated by the complex system in which the industry operates where chance combinations of multiple factors contribute to what are largely probabilistic (rather than deterministic) outcomes. Thus, some apparent successes are realized because of good fortune rather than good processes, and this research intends to bring attention to these events, the near‐misses. The processes that create these near‐misses could pose a threat if multiple contributing factors combine in adverse ways without the intervention of good fortune. Yet, near‐misses (if recognized as such) can, theoretically, offer a mechanism for continuing safety improvements, above and beyond learning gleaned from observable failure. We test whether or not this learning is apparent in the airline industry. Using data from 1990 to 2007, fixed effects Poisson regressions show that airlines learn from accidents (their own and others), and from one category of near‐misses—those where the possible dangers are salient. Unfortunately, airlines do not improve following near‐miss incidents when the focal event has no clear warnings of significant danger. Therefore, while airlines need to and can learn from certain near‐misses, we conclude with recommendations for improving airline learning from all near‐misses.     

Inflation and aggregate demand shocks

This paper derives and estimates a small general equilibrium model under the assumptions of imperfect competition and translog technology to simulate the impact of shifts in aggregate demand on prices. The simulations suggest that demand expansions are deflationary. This result challenges the common perception that the dynamic aggregate supply schedule is upward sloping.     

Bartlett's Test Applied to Variance Component Models

Exact methods for testing equality between variance components obtained from several cases of the same type of balanced orthogonal design are discussed. In particular, methods for successively testing equality of a number of components using Bartlett's tests are outlined for univariate and multivariate responses. Two clinical trial examples of repeated‐measures data are presented.     

Understanding the use of rural space: the need for multi-methods

Although the late 1990s saw increasing use of qualitative data in rural studies and a turn towards issues such as identities and the construction of rurality, many rural researchers still rely on a range of different methods and use both qualitative and quantitative data. However, the challenge of combining quantitative and qualitative data and using different methods is a theme not often dealt with in rural studies, at least not explicitly. This paper (re-)turns the attention to implications of using various methods and combining different types of data for studying a subject matter called ‘the use of rural space’. It concerns both physical land use and the practice and values of individual actors influencing the land use. We emphasise interplay between methodology and philosophy throughout the research process and argue for using multi-methods without compromising the integrity of the different methods. The methodological approach is a combined study of practice and values of individual actors. Two examples—one concerning Senegalese pastoralists’ livelihoods and their use of mobility and one concerning landowners’ location of field afforestation in Denmark—illustrate how the approach facilitates quite different studies of both practice and values and how quantitative and qualitative data can be combined in a non-eclectic way.