Critical mass (sociodynamics) In social dynamics, critical mass is a sufficient number of adopters of an innovation in a social system so that the rate of adoption becomes self-sustaining and creates further growth. It is an aspect of the theory of diffusion of innovations, written extensively on by Everett Rogers in his book Diffusion of Innovations.[1] Social factors influencing critical mass may involve the size, interrelatedness and level of communication in a society or one of its subcultures. Another is social stigma, or the possibility of public advocacy due to such a factor. Critical mass may be closer to majority consensus in political circles, where the most effective position is more often that held by the majority of people in society. Critical mass is a concept used in a variety of contexts, including physics, group dynamics, politics, public opinion, and technology. The concept of critical mass had existed before it entered a sociology context. Finally, Herbert A. In M. A fax machine
Human-based computation Human-based computation (HBC) is a computer science technique in which a machine performs its function by outsourcing certain steps to humans. This approach uses differences in abilities and alternative costs between humans and computer agents to achieve symbiotic human-computer interaction. In traditional computation, a human employs a computer[1] to solve a problem; a human provides a formalized problem description and an algorithm to a computer, and receives a solution to interpret. Human-based computation frequently reverses the roles; the computer asks a person or a large group of people to solve a problem, then collects, interprets, and integrates their solutions. Early work[edit] Human-based computation (apart from the historical meaning of "computer") research has its origins in the early work on interactive evolutionary computation. A concept of the automatic Turing test pioneered by Moni Naor (1996) is another precursor of human-based computation. Alternative terms[edit]
Plate-forme collaborative Un article de Wikipédia, l'encyclopédie libre. Une plate-forme de travail collaboratif est un espace de travail virtuel. C'est un outil, parfois sous la forme d'un site internet, qui centralise tous les outils liés à la conduite d'un projet, la gestion des connaissances ou au fonctionnement d'une organisation[1] et les met à disposition des acteurs. L'objectif du travail collaboratif est de faciliter et optimiser la communication entre les individus dans le cadre du travail ou d'une tâche non liée au travail, généralement en mesurant également leur impact sur le comportement des groupes. Contenus et fonctionnalités[modifier | modifier le code] Ce type de plate-forme intègre par exemple les fonctionnalités suivantes : Voir aussi[modifier | modifier le code] Usages des outils collaboratifs[modifier | modifier le code] Voir Etude de Kelton Research, juin 2010 Voir Etude de Lecko, décembre 2013 Liens externes[modifier | modifier le code] Articles connexes[modifier | modifier le code]
Notes on Factors in Collective Intelligence | There are probably hundreds of factors we could identify as important for the generation of collective intelligence in different types of human system. We find these factors wherever we see collective intelligence being exercised, and when we support them (especially in combination) we often find collective intelligence increasing. From my work with reflective forms of CI in groups, communities and societies, I find that about fifteen factors stand out most vividly, and I’ve listed them with brief descriptions here. As I tried to articulate them, I noticed how they overlapped and showed up as part of each other. _ _ _ _ _ __ _ Some Factors Which Support Collective Intelligence DIVERSITY – To the extent everyone is the same, their intelligence can’t collectively add up to something more than any of them individually. Like this: Like Loading...
information « relationary.wordpress I was passed this link to a free Knowledge Management Course by a friend today. I gave the entire course a read (it is not that long) and concluded that there was only one thing that the course covered that is not covered by the Six Hats, Six Coats as it has been explained so far. The issue is valuation, how do we know the cost/benefit of any fact. Otherwise, the authors wave the term “knowledge” around with little restraint to the point of its being meaningless. If they had it their way, everything would be knowledge. To perform valuation of the Six Hats, Six Coats Framework, facts are each of the Six Coats columns: Motive, Locale, Object, Method, Person and Moment. The rest of the Knowledge Management concepts are covered by the Six Hats, Six Coats Framework. The Six Hats, Six Coats Framework provides not only knowledge. Green Hat: Wisdom. The Six Hats, Six Coats Framework gives a clear definition of knowledge. “Mentifacts” and “Sociofacts” are obtuse terms.
Socially distributed cognition Distributed cognition is a psychological theory that knowledge lies not only within the individual, but also in the individual's social and physical environment. This theory was developed in the mid-1980s by Edwin Hutchins. Using insights from sociology, cognitive science, and the psychology of Vygotsky (cf. cultural-historical psychology) it emphasizes the social aspects of cognition. It is a framework for studying cognition rather than a type of cognition. Embodiment of information that is embedded in representations of interactionCoordination of enaction among embodied agentsEcological contributions to a cognitive ecosystem Distributed cognition is a branch of cognitive science that proposes that human knowledge and cognition are not confined to the individual. This abstraction can be categorized into three distinct types of processes: Early research[edit] John Milton Roberts thought that social organization could be seen as cognition through a community (Roberts 1964). Daniel L.
Pro-Ams: The Rise Of The Amateur Professionals, Prosumers, Passionate Amateurs "A number of factors are coming together to empower amateurs in a way never before possible, blurring the lines between those who make and those who take. Unlike the dot-com fortune hunters of the late 1990s, these do-it-yourselfers aren't deluding themselves with oversized visions of what they might achieve. Instead, they're simply finding a way--in this mass-produced, Wal-Mart world--to take power back, prove that they can make the products that they want to consume, have fun doing so, and, just maybe, make a few dollars." Passionate amateurs have in fact attracted the attention of both large corporations as well as the one of mainstream news sources, who have recently started to devote quite a bit of attention to this new spreading phenomenon. Call them "prosumers" or "Pro-Am", professional amateurs are here to stay while gradually transforming many of the professional realities we now give for granted. "Numerous currents have converged to produce this reaction.
User innovation User innovation refers to innovation by intermediate users (e.g. user firms) or consumer users (individual end-users or user communities), rather than by suppliers (producers or manufacturers).[1] Eric von Hippel [2] and others observed that many products and services are actually developed or at least refined, by users, at the site of implementation and use. These ideas are then moved back into the supply network. This is because products are developed to meet the widest possible need; when individual users face problems that the majority of consumers do not, they have no choice but to develop their own modifications to existing products, or entirely new products, to solve their issues. Based on research on the evolution of Internet technologies and open source software Ilkka Tuomi (Tuomi 2002) further highlighted the point that users are fundamentally social. See also[edit] [edit] Sources[edit] Bilgram, V.; Brem, A.; Voigt, K. External links[edit]
Amateur professionalism Amateur professionalism or professional amateurism (shortened to am pro, AmPro, Am-Pro, pro am, ProAm, Pro-Am, etc.) is a socioeconomic concept that describes a blurring of the distinction between professional and amateur within any endeavour or attainable skill that could be labelled professional, whether it is in the field of writing, computer programming, music, film, etc. When speaking of persons, the terms amateur professionals, amateur pros, am pros, professional amateurs, professional ams or pro ams may be used. The idea is distinct from the sports term "pro–am" (professional–amateur), though related to and ultimately derived from it. Amateur professionalism occurs in populations that have more leisure time and live longer, allowing the pursuit of hobbies and other non-essential interests at a professional or near-professional knowledge- and skill-level. See also[edit] User innovation References[edit] Further reading[edit]
Pro–am Pro–am (or pro/am, pro am, ProAm; a contraction of professional–amateur) is a mix of professional and amateur competition within a sport or collaboration between professionals and amateurs in a scientific discipline, such as astronomy.[1] In reference to players, the term thus also implies a status (official or otherwise) that is intermediate, indeterminate or fluctuating between amateur and professional, rather than simply implying amateur activity at a professional level or vice versa, ideas more related to the similar socio-economic term "amateur professionalism". A common synonym for some uses of "pro–am" is semi-professional (semi-pro). The term has long had various meanings and significances, depending upon the sport in question. Pro–am competition is especially common in golf[clarification needed] and track and field.
Système complexe adaptatif Un article de Wikipédia, l'encyclopédie libre. Complex Adaptive System Un système complexe adaptatif ou système complexe auto-adaptatif est l'ensemble des cas particuliers d'un système complexe capable de s'adapter à son environnement par des expériences d'apprentissage. Le terme anglais complex adaptive systems (CAS) a été introduit par l'Institut interdisciplinaire de Santa Fe notamment par John H. Holland et Murray Gell-Mann. Observations[modifier | modifier le code] En 1962, Vero Copner Wynne-Edwards a observé la sélection de groupe à l’œuvre dans les communautés d’oiseaux sauvages. Par ailleurs, David Sloan Wilson (en) a démontré qu’un réseau social qui applique les règles du « système adaptatif complexe » constitue la plus puissante machine à apprendre et gagne presque à tous les coups[1]. Exemples[modifier | modifier le code] Notes et références[modifier | modifier le code] ↑ (fr) Le principe de Lucifer : le cerveau global, Howard Bloom (trad.
Complex adaptive system They are complex in that they are dynamic networks of interactions, and their relationships are not aggregations of the individual static entities. They are adaptive in that the individual and collective behavior mutate and self-organize corresponding to the change-initiating micro-event or collection of events.[1][2] Overview[edit] The term complex adaptive systems, or complexity science, is often used to describe the loosely organized academic field that has grown up around the study of such systems. Complexity science is not a single theory— it encompasses more than one theoretical framework and is highly interdisciplinary, seeking the answers to some fundamental questions about living, adaptable, changeable systems. The fields of CAS and artificial life are closely related. The study of CAS focuses on complex, emergent and macroscopic properties of the system.[3][11][12] John H. General properties[edit] Characteristics[edit] Robert Axelrod & Michael D. Modeling and Simulation[edit]
Les Shadoks Un article de Wikipédia, l'encyclopédie libre. Les Shadoks Titre de la série Les Shadoks. Synopsis[modifier | modifier le code] La série relate les différentes histoires et mésaventures des Shadoks, des êtres anthropomorphes aux apparences d'oiseaux (à ce jour, toujours non-identifiés) rondouillards possédant de longues pattes et de petites ailes ridicules. Les Shadoks ont pour ennemis principaux — ou plutôt comme rivaux[pas clair] — les Gibis qui leur sont intellectuellement supérieurs. Les Shadoks possèdent pour tout vocabulaire quatre mots monosyllabiques : « Ga, Bu, Zo, Meu ». Genèse[modifier | modifier le code] Avant les Shadoks[modifier | modifier le code] Jacques Rouxel propose[Quand ?] Prémices[modifier | modifier le code] Réalisation[modifier | modifier le code] Réception[modifier | modifier le code] Séries[modifier | modifier le code] Les trois premières séries n'ont jamais eu de titre officiel[8] et la quatrième série est nommée « Les Shadoks et le big blank ».