Krange, O., & Skogen, K. (2011). When the lads go hunting: The 'Hammertown mechanism' and the conflict over wolves in Norway. Ethnography, 12(4), 466–489.
Abstract: Rural communities are changing. Depopulation and unemployment is accompanied by the advance of new perspectives on nature, where protection trumps resource extraction. These developments are perceived as threatening by rural working-class people with close ties to traditional land use ? a situation they often meet with cultural resistance. Cultural resistance is not necessarily launched against institutionalized power, nor does it necessarily imply a desire for fundamental social change. It should rather be seen as a struggle for autonomy. However, autonomy does not entail influence outside the cultural realm. Struggles to uphold traditional rural lifestyles ? for example by denouncing the current nature conservation regime ? could be understood in much the same conceptual framework as Willis employed in ?Learning to labour?. Based on an ethnographic study of the conflicts over wolf protection, we demonstrate that ?the Hammertown mechanism? is of a more general nature than often implied in the discussion of Willis? work.
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A. Wiggins, & K. Crowston. (2011). From Conservation to Crowdsourcing: A Typology of Citizen Science. In 2011 44th Hawaii International Conference on System Sciences (pp. 1–10). 2011 44th Hawaii International Conference on System Sciences.
Abstract: Citizen science is a form of research collaboration involving members of the public in scientific research projects to address real-world problems. Often organized as a virtual collaboration, these projects are a type of open movement, with collective goals addressed through open participation in research tasks. Existing typologies of citizen science projects focus primarily on the structure of participation, paying little attention to the organizational and macrostructural properties that are important to designing and managing effective projects and technologies. By examining a variety of project characteristics, we identified five types-Action, Conservation, Investigation, Virtual, and Education- that differ in primary project goals and the importance of physical environment to participation.
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Bücheler, T., & Sieg, J. H. (2011). Understanding Science 2.0: Crowdsourcing and Open Innovation in the Scientific Method. Proceedings of the 2nd European Future Technologies Conference and Exhibition 2011 (FET 11), 7, 327–329.
Abstract: The innovation process is currently undergoing significant change in many industries. The World Wide Web has created a virtual world of collective intelligence and helped large groups of people connect and collaborate in the innovation process [1]. Von Hippel [2], for instance, states that a large number of users of a given technology will come up with innovative ideas. This process, originating in business, is now also being observed in science. Discussions around “Citizen Science” [3] and “Science 2.0” [4] suggest the same effects are relevant for fundamental research practices. “Crowdsourcing” [5] and “Open Innovation” [6] as well as other names for those paradigms, like Peer Production, Wikinomics, Swarm Intelligence etc., have become buzzwords in recent years. However, serious academic research efforts have also been started in many disciplines. In essence, these buzzwords all describe a form of collective intelligence that is enabled by new technologies, particularly internet connectivity. The focus of most current research on this topic is in the for-profit domain, i.e. organizations willing (and able) to pay large sums to source innovation externally, for instance through innovation contests. Our research is testing the applicability of Crowdsourcing and some techniques from Open Innovation to the scientific method and basic science in a non-profit environment (e.g., a traditional research university). If the tools are found to be useful, this may significantly change how some research tasks are conducted: While large, apriori unknown crowds of “irrational agents” (i.e. humans) are used to support scientists (and teams thereof) in several research tasks through the internet, the usefulness and robustness of these interactions as well as scientifically important factors like quality and validity of research results are tested in a systematic manner. The research is highly interdisciplinary and is done in collaboration with scientists from sociology, psychology, management science, economics, computer science, and artificial intelligence. After a pre-study, extensive data collection has been conducted and the data is currently being analyzed. The paper presents ideas and hypotheses and opens the discussion for further input.
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Stenglein, J. L., Waits, L. P., Ausband, D. E., Zager, P., & Mack, C. M. (2011). Estimating gray wolf pack size and family relationships using non invasive genetic sampling at rendezvous sites. J Mammal, 92.
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Core Development Team, R. (2011). R: a language and environment for statistical computing. Vienna, Austria: R foundation for statistical computing.
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Marescot, L., Pradel, R., Duchamp, C., Cubaynes, S., Mrboutin, E., & Choquet, R. (2011). Capture – recapture population growth rate as a robust tool against detection heterogeneity for population management. Ecol Appl, 21.
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Morgan, T. W., & Elliott, C. L. (2011). Comparison of remotely-triggered cameras vs. howling surveys for estimating coyote (Canis latrans) Abundance in central Kentucky. J Ky Acad Science, 72.
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Morand-Ferron, J., & Quinn, J. L. (2011). Larger groups of passerines are more efficient problem solvers in the wild. Proc Natl Acad Sci USA, 108(38), 15898–15903.
Abstract: Group living commonly helps organisms face challenging environmental conditions. Although a known phenomenon in humans, recent findings suggest that a benefit of group living in animals generally might be increased innovative problem-solving efficiency. This benefit has never been demonstrated in a natural context, however, and the mechanisms underlying improved efficiency are largely unknown. We examined the problem-solving performance of great and blue tits at automated devices and found that efficiency increased with flock size. This relationship held when restricting the analysis to naive individuals, demonstrating that larger groups increased innovation efficiency. In addition to this effect of naive flock size, the presence of at least one experienced bird increased the frequency of solving, and larger flocks were more likely to contain experienced birds. These findings provide empirical evidence for the “pool of competence” hypothesis in nonhuman animals. The probability of success also differed consistently between individuals, a necessary condition for the pool of competence hypothesis. Solvers had a higher probability of success when foraging with a larger number of companions and when using devices located near rather than further from protective tree cover, suggesting a role for reduced predation risk on problem-solving efficiency. In contrast to traditional group living theory, individuals joining larger flocks benefited from a higher seed intake, suggesting that group living facilitated exploitation of a novel food source through improved problem-solving efficiency. Together our results suggest that both ecological and social factors, through reduced predation risk and increased pool of competence, mediate innovation in natural populations.
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Miyata, H., Gajdon, G. K., Huber, L., & Fujita, K. (2011). How do keas (Nestor notabilis) solve artificial-fruit problems with multiple locks? Anim. Cogn., 14(1), 45–58.
Abstract: Keas, a species of parrots from New Zealand, are an interesting species for comparative studies of problem solving and cognition because they are known not only for efficient capacities for object manipulation but also for explorative and playful behaviors. To what extent are they efficient or explorative, and what cognitive abilities do they use? We examined how keas would solve several versions of artificial-fruit box problems having multiple locks. After training keas to remove a metal rod from over a Plexiglas lid that had to be opened, we exposed the birds to a variety of tasks having two or more locks. We also introduced a preview phase during which the keas had extended opportunity to look at the tasks before the experimenter allowed the birds to solve them, to examine whether the preview phase would facilitate the birds' performance on the tasks. In a large number of tests, the keas showed a strong trend to solve the tasks with no positive effect of previewing the tasks. When the tasks became complex, however, the keas corrected inappropriate responses more quickly when they had had chance to preview the problems than when they had not. The results suggest that the keas primarily used explorative strategies in solving the lock problems but might have obtained some information about the tasks before starting to solve them. This may reflect a good compromise of keas' trial-and-error tendency and their good cognitive ability that result from a selection pressure they have faced in their natural habitat.
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Hendriksen, P., Elmgreen, K., & Ladewig, J. (2011). Trailer-loading of horses: Is there a difference between positive and negative reinforcement concerning effectiveness and stress-related signs? J. Vet. Behav., 6(5), 261–266.
Abstract: The traditional way to train horses is by the application of negative reinforcement (NR). In the past few years, however, the use of positive reinforcement (PR) has become more common. To evaluate the effectiveness and the possible stressor effect of the 2 training methods, 12 horses showing severe trailer-loading problems were selected and exposed to trailer-loading. They were randomly assigned to one of the 2 methods. NR consisted of various degrees of pressure (lead rope pulling, whip tapping). Pressure was removed as soon as the horse complied. PR horses were exposed to clicker training and taught to follow a target into the trailer. Heart rate (HR) was recorded every 5 seconds and behavior denoting discomfort was observed using one-zero sampling with 10 seconds sampling intervals. Training was completed when the horse could enter the trailer upon a signal, or was terminated after a maximum of 15 sessions. Of the 12 horses, 10 reached the criterion within the 15 sessions. One horse was eliminated from the study because of illness and 1 PR horse failed to enter the trailer. A Mann-Whitney U-test indicated that the horses trained with NR displayed significantly more discomfort behavior per training session than horses trained with PR (NR: 13.26 ± 3.25; PR: 3.17 ± 8.93, P < 0.0001) and that horses in the PR group spent less time (second) per session to complete the training criterion (NR: 672.9 ± 247.12; PR: 539.81 ± 166.37, P < 0.01). A Mann-Whitney U-test showed that no difference existed in mean HR (bpm) between the 2 groups (NR: 53.06 ± 11.73 bpm; PR: 55.54 ± 6.7 bpm, P > 0.05), but a Wilcoxon test showed a difference in the PR group between the baseline of HR and mean HR obtained during training sessions (baseline PR: 43 ± 8.83 bpm; PR: 55.54 ± 6.7 bpm, P < 0.05). In conclusion, the PR group provided the fastest training solution and expressed less stress response. Thus, the PR procedure could provide a preferable training solution when training horses in potentially stressing situations.
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