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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Artzy-Randrup, Y., Fleishman, S. J., Ben-Tal, N., & Stone, L. (2004). Comment on “Network Motifs: Simple Building Blocks of Complex Networks” and “Superfamilies of Evolved and Designed Networks”. Science, 305(5687), 1107c.
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Ash, C., Chin, G., Pennisi, E., & Sugden, A. (2007). Living in Societies. Science, 317(5843), 1337–.
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Axelrod, R., & Hamilton, W. D. (1981). The evolution of cooperation. Science, 211(4489), 1390–1396.
Abstract: Cooperation in organisms, whether bacteria or primates, has been a difficulty for evolutionary theory since Darwin. On the assumption that interactions between pairs of individuals occur on a probabilistic basis, a model is developed based on the concept of an evolutionarily stable strategy in the context of the Prisoner's Dilemma game. Deductions from the model, and the results of a computer tournament show how cooperation based on reciprocity can get started in an asocial world, can thrive while interacting with a wide range of other strategies, and can resist invasion once fully established. Potential applications include specific aspects of territoriality, mating, and disease.
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Bartal, I. B. - A., Decety, J., & Mason, P. (2011). Empathy and Pro-Social Behavior in Rats. Science, 334(6061), 1427–1430.
Abstract: Whereas human pro-social behavior is often driven by empathic concern for another, it is unclear whether nonprimate mammals experience a similar motivational state. To test for empathically motivated pro-social behavior in rodents, we placed a free rat in an arena with a cagemate trapped in a restrainer. After several sessions, the free rat learned to intentionally and quickly open the restrainer and free the cagemate. Rats did not open empty or object-containing restrainers. They freed cagemates even when social contact was prevented. When liberating a cagemate was pitted against chocolate contained within a second restrainer, rats opened both restrainers and typically shared the chocolate. Thus, rats behave pro-socially in response to a conspecific�s distress, providing strong evidence for biological roots of empathically motivated helping behavior.
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Bednarz, J. C. (1988). Cooperative Hunting Harris' Hawks (Parabuteo unicinctus). Science, 239(4847), 1525–1527.
Abstract: Coordinated hunting by several individuals directed toward the capture and sharing of one Large prey animal has been documented convincingly only for a few mammalian carnivores. In New Mexico, Harris' hawks formed hunting parties of two to six individuals in the nonbreeding season. This behavior improved capture success and the average energy available per individual enabled hawks to dispatch prey larger than themselves. These patterns suggest that cooperation is important to understanding the evolution of complex social behavior in higher vertebrates and, specifically, that benefits derived from team hunting a key factor in the social living of Harris' hawks.
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Berger J,. (1983). Ecology and catastrophic mortality in wild horses: Implantations for interpreting fossil assemblages. Science 220, , 1403–1404.
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Bergman, T. J., Beehner, J. C., Cheney, D. L., & Seyfarth, R. M. (2003). Hierarchical classification by rank and kinship in baboons. Science, 302(5648), 1234–1236.
Abstract: Humans routinely classify others according to both their individual attributes, such as social status or wealth, and membership in higher order groups, such as families or castes. They also recognize that people's individual attributes may be influenced and regulated by their group affiliations. It is not known whether such rule-governed, hierarchical classifications are specific to humans or might also occur in nonlinguistic species. Here we show that baboons recognize that a dominance hierarchy can be subdivided into family groups. In playback experiments, baboons respond more strongly to call sequences mimicking dominance rank reversals between families than within families, indicating that they classify others simultaneously according to both individual rank and kinship. The selective pressures imposed by complex societies may therefore have favored cognitive skills that constitute an evolutionary precursor to some components of human cognition.
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BERNITSCHKE K et al,. (1965). Chromosome complement: differences between Equus caballus and Equus przewalskii, Poliakoff. Science, 148, 382.
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Blaisdell, A. P., Sawa, K., Leising, K. J., & Waldmann, M. R. (2006). Causal reasoning in rats. Science, 311(5763), 1020–1022.
Abstract: Empirical research with nonhuman primates appears to support the view that causal reasoning is a key cognitive faculty that divides humans from animals. The claim is that animals approximate causal learning using associative processes. The present results cast doubt on that conclusion. Rats made causal inferences in a basic task that taps into core features of causal reasoning without requiring complex physical knowledge. They derived predictions of the outcomes of interventions after passive observational learning of different kinds of causal models. These competencies cannot be explained by current associative theories but are consistent with causal Bayes net theories.
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