Struggles Over Legitimacy in Global Organizational Restructuring: A Rhetorical Perspective on Legitimation Strategies and Dynamics in a Shutdown Case

Critical organization scholars have focused increasing attention on industrial and organizational restructurings such as shutdown decisions. However, little is known about the rhetorical strategies used to legitimate or resist plant closures in organizational negotiations. In this article, we draw from New Rhetoric to analyze rhetorical struggles, strategies and dynamics in unfolding organizational negotiations. We focus on the shutdown of the bus body unit of the Sweden-based Volvo Bus Corporation in Finland. We distinguish five types of rhetorical legitimation strategies and dynamics. These include the three classical dynamics of logos (rational arguments), pathos (emotional moral arguments), and ethos (authority-based arguments), but also autopoiesis (autopoietic narratives), and cosmos (cosmological constructions). Our analysis contributes to previous studies on organizational restructuring by providing a more nuanced understanding of how contemporary industrial closures are legitimated and resisted in organizational negotiations. This study also increases theoretical understanding of the role of rhetoric in legitimation more generally.

Effect of soil preparation of boreal spruce forest on air and soil temperature conditions in forest regeneration areas.

The effect of scarification, ploughing and cross-directional plouhing on temperature conditions in the soil and adjacent air layer have been studied during 11 consecutive growth periods by using an unprepared clear-cut area as a control site. The maximum and minimum temperatures were measured daily in the summer months, and other temperature observations were made at four-hour intervals by means of a Grant measuring instrument. The development of the seedling stand was also followed in order to determine its shading effect on the soil surface. Soil preparation decreased the daily temperature amplitude of the air at the height of 10 cm. The maximum temperatures on sunny days were lower in the tilts of the ploughed and in the humps of the cross-directional ploughed sites compared with the unprepared area. Correspondingly, the night temperatures were higher and so the soil preparation considerably reduced the risk of night frost. In the soil at the depth of 5 cm, soil preparation increased daytime temperatures and reduced night temperatures compared with unprepared area. The maximum increase in monthly mean temperatures was almost 5 °C, and the daily variation in the surface parts of the tilts and humps increased so that excessively high temperatures for the optimal growth of the root system were measured from time to time. The temperature also rose at the depths of 50 and 100 cm. Soil preparation also increased the cumulative temperature sum. The highest sums accumulated during the summer months were recorded at the depth of 5 cm in the humps of cross-directional ploughed area (1127 dd.) and in the tilts of the ploughed area (1106 dd.), while the corresponding figure in the unprepared soil was 718 dd. At the height of 10 cm the highest temperature sum was 1020 dd. in the hump, the corresponding figure in the unprepared area being 925 dd. The incidence of high temperature amplitudes and percentage of high temperatures at the depth of 5 cm decreased most rapidly in the humps of cross-directional ploughed area and in the ploughing tilts towards the end of the measurement period. The decrease was attributed principally to the compressing of tilts, the ground vegetation succession and the growth of seedlings. The mean summer temperature in the unprepared area was lower than in the prepared area and the difference did not diminish during the period studied. The increase in temperature brought about by soil preparation thus lasts at least more than 10 years.

Paradigms in Statistical Inference for Finite Populations; Up to the 1950s

Modern sample surveys started to spread after statistician at the U.S. Bureau of the Census in the 1940s had developed a sampling design for the Current Population Survey (CPS). A significant factor was also that digital computers became available for statisticians. In the beginning of 1950s, the theory was documented in textbooks on survey sampling. This thesis is about the development of the statistical inference for sample surveys. For the first time the idea of statistical inference was enunciated by a French scientist, P. S. Laplace. In 1781, he published a plan for a partial investigation in which he determined the sample size needed to reach the desired accuracy in estimation. The plan was based on Laplace s Principle of Inverse Probability and on his derivation of the Central Limit Theorem. They were published in a memoir in 1774 which is one of the origins of statistical inference. Laplace s inference model was based on Bernoulli trials and binominal probabilities. He assumed that populations were changing constantly. It was depicted by assuming a priori distributions for parameters. Laplace s inference model dominated statistical thinking for a century. Sample selection in Laplace s investigations was purposive. In 1894 in the International Statistical Institute meeting, Norwegian Anders Kiaer presented the idea of the Representative Method to draw samples. Its idea was that the sample would be a miniature of the population. It is still prevailing. The virtues of random sampling were known but practical problems of sample selection and data collection hindered its use. Arhtur Bowley realized the potentials of Kiaer s method and in the beginning of the 20th century carried out several surveys in the UK. He also developed the theory of statistical inference for finite populations. It was based on Laplace s inference model. R. A. Fisher contributions in the 1920 s constitute a watershed in the statistical science He revolutionized the theory of statistics. In addition, he introduced a new statistical inference model which is still the prevailing paradigm. The essential idea is to draw repeatedly samples from the same population and the assumption that population parameters are constants. Fisher s theory did not include a priori probabilities. Jerzy Neyman adopted Fisher s inference model and applied it to finite populations with the difference that Neyman s inference model does not include any assumptions of the distributions of the study variables. Applying Fisher s fiducial argument he developed the theory for confidence intervals. Neyman s last contribution to survey sampling presented a theory for double sampling. This gave the central idea for statisticians at the U.S. Census Bureau to develop the complex survey design for the CPS. Important criterion was to have a method in which the costs of data collection were acceptable, and which provided approximately equal interviewer workloads, besides sufficient accuracy in estimation.