Social democracy, embeddedness and decommodification: On the conceptual innovations and intellectual affiliations of Karl Polanyi

Of the several debates that revolve around the work of the economic historian and political economist Karl Polanyi, one that continues to exercise minds concerns his analysis of, and political attitudes toward, post-war capitalism and the welfare state. Simplified a little, it is a debate with two sides. To borrow Iván Szelényi's terms, one side constructs a ‘hard’ Karl Polanyi, the other a ‘soft’ one. The former advocated a socialist mixed economy dominated by redistributive mechanisms. He was a radical socialist for whom the market should never be the dominant mechanism of economic coordination. His ‘soft’ alter ego insisted that the market system remain essentially intact but be complemented by redistributive mechanisms. The ‘double movement’ – the central thesis of his ‘Great Transformation’ – acts, in this reading, as a self-correcting mechanism that moderates the excesses of market fundamentalism; its author was positioned within the social-democratic mainstream for which the only realistic desirable goal is a regulated form of capitalism. In terms of textual evidence there is much to be said for both interpretations. In this article I suggest a different approach, one that focuses upon the meaning of Polanyi's concepts in relation to their socio-political and intellectual environment

Simulating a base population in honey bee for molecular genetic studies

<p>Abstract</p> <p>Background</p> <p>Over the past years, reports have indicated that honey bee populations are declining and that infestation by an ecto-parasitic mite (<it>Varroa destructor</it>) is one of the main causes. Selective breeding of resistant bees can help to prevent losses due to the parasite, but it requires that a robust breeding program and genetic evaluation are implemented. Genomic selection has emerged as an important tool in animal breeding programs and simulation studies have shown that it yields more accurate breeding value estimates, higher genetic gain and low rates of inbreeding. Since genomic selection relies on marker data, simulations conducted on a genomic dataset are a pre-requisite before selection can be implemented. Although genomic datasets have been simulated in other species undergoing genetic evaluation, simulation of a genomic dataset specific to the honey bee is required since this species has a distinct genetic and reproductive biology. Our software program was aimed at constructing a base population by simulating a random mating honey bee population. A forward-time population simulation approach was applied since it allows modeling of genetic characteristics and reproductive behavior specific to the honey bee.</p> <p>Results</p> <p>Our software program yielded a genomic dataset for a base population in linkage disequilibrium. In addition, information was obtained on (1) the position of markers on each chromosome, (2) allele frequency, (3) χ² statistics for Hardy-Weinberg equilibrium, (4) a sorted list of markers with a minor allele frequency less than or equal to the input value, (5) average r² values of linkage disequilibrium between all simulated marker loci pair for all generations and (6) average r² value of linkage disequilibrium in the last generation for selected markers with the highest minor allele frequency.</p> <p>Conclusion</p> <p>We developed a software program that takes into account the genetic and reproductive biology specific to the honey bee and that can be used to constitute a genomic dataset compatible with the simulation studies necessary to optimize breeding programs. The source code together with an instruction file is freely accessible at <url>http://msproteomics.org/Research/Misc/honeybeepopulationsimulator.html</url></p

Mixing of Honeybees with Different Genotypes Affects Individual Worker Behavior and Transcription of Genes in the Neuronal Substrate

Division of labor in social insects has made the evolution of collective traits possible that cannot be achieved by individuals alone. Differences in behavioral responses produce variation in engagement in behavioral tasks, which as a consequence, generates a division of labor. We still have little understanding of the genetic components influencing these behaviors, although several candidate genomic regions and genes influencing individual behavior have been identified. Here, we report that mixing of worker honeybees with different genotypes influences the expression of individual worker behaviors and the transcription of genes in the neuronal substrate. These indirect genetic effects arise in a colony because numerous interactions between workers produce interacting phenotypes and genotypes across organisms. We studied hygienic behavior of honeybee workers, which involves the cleaning of diseased brood cells in the colony. We mixed ∼500 newly emerged honeybee workers with genotypes of preferred Low (L) and High (H) hygienic behaviors. The L/H genotypic mixing affected the behavioral engagement of L worker bees in a hygienic task, the cooperation among workers in uncapping single brood cells, and switching between hygienic tasks. We found no evidence that recruiting and task-related stimuli are the primary source of the indirect genetic effects on behavior. We suggested that behavioral responsiveness of L bees was affected by genotypic mixing and found evidence for changes in the brain in terms of 943 differently expressed genes. The functional categories of cell adhesion, cellular component organization, anatomical structure development, protein localization, developmental growth and cell morphogenesis were overrepresented in this set of 943 genes, suggesting that indirect genetic effects can play a role in modulating and modifying the neuronal substrate. Our results suggest that genotypes of social partners affect the behavioral responsiveness and the neuronal substrate of individual workers, indicating a complex genetic architecture underlying the expression of behavior

Regular dorsal dimples and damaged mites of Varroa destructor in some Iranian honey bees (Apis mellifera)

The frequency of damaged Varroadestructor Anderson and Trueman (Mesostigmata: Varroidae) found on the bottom board of hives of the honey bee, Apis mellifera L. (Hymenoptera: Apidae) has been used as an indicator of the degree of tolerance or resistance of honey bee colonies against mites. However, it is not clear that this measure is adequate. These injuries should be separated from regular dorsal dimples that have a developmental origin. To investigate damage to Varroa mites and regular dorsal dimples, 32 honey bee (A. mellifera) colonies were selected from four Iranian provinces: Isfahan, Markazi, Qazvin, and Tehran. These colonies were part of the National Honey bee Breeding Program that resulted in province-specific races. In April, Varroa mites were collected from heavily infested colonies and used to infest the 32 experimental colonies. In August, 20 of these colonies were selected (five colonies from each province). Adult bees from these colonies were placed in cages and after introducing mites, damaged mites were collected from each cage every day. The average percentage of injured mites ranged from 0.6 to 3.0% in four provinces. The results did not show any statistical differences between the colonies within provinces for injuries to mites, but there were some differences among province-specific lines. Two kinds of injuries to the mites were observed: injuries to legs and pedipalps, and injuries to other parts of the body. There were also some regular dorsal dimples on dorsal idiosoma of the mites that were placed in categories separate from mites damaged by bees. This type of classification helps identifying damage to mites and comparing them with developmental origin symptoms, and may provide criteria for selecting bees tolerant or resistant to this mite

Investigating the Effect of Conflicting Goals and Transparency on Trust and Collaboration in Multi-Team Systems

In Air Traffic Management (ATM) multiple teams have to collaborate to achieve efficient and safe operation. Multiple-team operations rely on communication and information sharing between the team members. In this field, multi-team systems (MTSs) are the most common form of organization. The interface between the organizations involved (e.g. air traffic control, cockpit crews, airports) is of central importance. Apart from a common goal, different stakeholders may pursue individual goals governed by their own company culture or policies. Therefore, simply sharing all available information may not be enough to ensure safe and efficient operation. As part of the project ITC (Inter-Team Collaboration), an experimental study with 48 teams of three (n=144) has just started to investigate the impact that conflicting goals have on communication and collaboration. Additionally, it examines whether and how transparency in roles, processes, and goals can affect performance, communication, and trust in multi-team systems. In the synthetic task environment (STE) ConCenT (Control Center Task Environment), teams of three have to collaborate to detect system failures in time, determine their causes, and decide on a solution in order to ensure successful production processes. Measurements of performance, perceived trust, communication, and gaze data will be analyzed to examine and compare different coordination and communication patterns on a group level. Results of the study will identify factors that may facilitate or hinder collaborative work processes in an MTS, thus enabling the validation of an approach to improve collaboration through transparency and mutual trust

Genetic parameters for five traits in Africanized honeybees using Bayesian inference

Heritability and genetic correlations for honey (HP) and propolis production (PP), hygienic behavior (HB), syrup-collection rate (SCR) and percentage of mites on adult bees (PMAB) of a population of Africanized honeybees were estimated. Data from 110 queen bees over three generations were evaluated. Single and multi-trait models were analyzed by Bayesian Inference using MTGSAM. The localization of the hive was significant for SCR and HB and highly significant for PP. Season-year was highly significant only for SCR. The number of frames with bees was significant for HP and PP, including SCR. The heritability estimates were 0.16 for HP, 0.23 for SCR, 0.52 for HB, 0.66 for PP, and 0.13 for PMAB. The genetic correlations were positive among productive traits (PP, HP and SCR) and negative between productive traits and HB, except between PP and HB. Genetic correlations between PMAB and other traits, in general, were negative, except with PP. The study permitted to identify honeybees for improved propolis and honey production. Hygienic behavior may be improved as a consequence of selecting for improved propolis production. The rate of syrup consumption and propolis production may be included in a selection index to enhance honeybee traits

Heritabilities for several colony traits in the honeybee (Apis mellifera carnica)

Colony traits in honeybees result from the sum of the queen contribution and of an average contribution of the workers. To estimate separately the heritability of queen and worker effects, observed covariances of related colonies are expressed as functions of theoretical causal components of phenotypic variance. Covariances were estimated by REML (Restricted Maximum Likelihood) and weighted parent-offspring covariance analysis. Causal components are estimated by weighted least squares analysis of this system of equations. The data (n = 5 581) come from an Apis mellifera carnica population in northern and mid-Germany. Honey and wax production have medium h2 values for worker (0.26/0.39) and queen effects (0.15/0.45). The corresponding values for aggressiveness, calmness during examination and spring development were higher. Strongly negative genetic correlations were found between worker and queen effects with respect to all colony traits. This negative genetic relationship impedes selection response, since it reduces the phenotypic variance within population, and therefore tends to stabilize it at a particular value