149 resultados para Collective representations


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Past studies relate small business advisory program effectiveness to advisory characteristics such as advisory intensity and scope. We contribute to existing literature by seeking to identify the impact of different advisory program methods of delivery on learning and subsequent firm innovation behavior. Our research is based on a survey of 257 Australian firms completing small business advisory programs in the three years preceding the research. We explore the range of small business advisory program delivery methods in which our surveyed firms participated and, with reference to the literature on organizational learning and innovation, we analyze predictors of firms' learning ability and innovativeness based on the identified delivery methods. First, we found that business advisory programs that involved high levels of collective learning and tailored approaches enhanced firms' perceptions of their learning of critical skills or capabilities. We also found that small business advisory programs that were delivered by using practice-based approaches enhanced firms' subsequent organizational innovation. We verified this finding by testing whether firms that have participated in small business advisory services subsequently demonstrate improved behavior in terms of organizational innovativeness, when compared with matched firms that have not participated in an advisory program.

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Process models describe someone’s understanding of processes. Processes can be described using unstructured, semi-formal or diagrammatic representation forms. These representations are used in a variety of task settings, ranging from understanding processes to executing or improving processes, with the implicit assumption that the chosen representation form will be appropriate for all task settings. We explore the validity of this assumption by examining empirically the preference for different process representation forms depending on the task setting and cognitive style of the user. Based on data collected from 120 business school students, we show that preferences for process representation formats vary dependent on application purpose and cognitive styles of the participants. However, users consistently prefer diagrams over other representation formats. Our research informs a broader research agenda on task-specific applications of process modeling. We offer several recommendations for further research in this area.

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The study of data modelling with elementary students involves the analysis of a developmental process beginning with children’s investigations of meaningful contexts: visualising, structuring, and representing data and displaying data in simple graphs (English, 2012; Lehrer & Schauble, 2005; Makar, Bakker, & Ben-Zvi, 2011). A 3-year longitudinal study investigated young children’s data modelling, integrating mathematical and scientific investigations. One aspect of this study involved a researcher-led teaching experiment with 21 mathematically able Grade 1 students. The study aimed to describe explicit developmental features of students’ representations of continuous data...

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The print media play a vital role in informing the public about child abuse and neglect. This information helps build broad support for laws and system developments that enable the state to intervene into private family lives and ensure that children are protected from maltreatment. Print media coverage usually sets the daily media agenda. It therefore influences public understandings of child abuse and neglect and what people believe should be done about it. Media impact on policy agendas should not be underestimated. This article outlines the results of a study of all major Australian newspaper stories covering abuse and neglect matters during an 18-month period in 2008–2009. A range of issues are identified concerning how well these stories inform the public about the nature of the problem and the current national reform agenda for protective systems that promotes early intervention and prevention...

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From the early literature on the role of firm managers (Alchian and Demsetz 1972) to the industrial organisation on contracts and mechanism design (Laont and Martimort 2009), economists have given a lot of attention to find solutions to the imperfect alignment between individuals' incentives and an organisation's collective goals (Prendergast 1999). In that literature a key role of managers is to monitor individuals to reward behaviour aligned with the collective goals and reduce sub- optimal behaviour, such as shirking. How- ever, another strand of literature, since Akerlof (1982), has put forward a vision of reciprocal behaviour between an organisation's leadership and its members: gifts (high wages, recognition) from the organisation are reciprocated by high effort from the members of the organisation. By rewarding individual members (rather than strictly monitoring them), organisations may benefit from greater effort and cohesion. Experimental research in organizational economics has provided mixed results suggesting that agents do react to personal incentives but also that reciprocal behaviour can play a substantial role (Camerer and Weber 2012).

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It is not uncommon to hear a person of interest described by their height, build, and clothing (i.e. type and colour). These semantic descriptions are commonly used by people to describe others, as they are quick to relate and easy to understand. However such queries are not easily utilised within intelligent surveillance systems as they are difficult to transform into a representation that can be searched for automatically in large camera networks. In this paper we propose a novel approach that transforms such a semantic query into an avatar that is searchable within a video stream, and demonstrate state-of-the-art performance for locating a subject in video based on a description.

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Wound healing and tumour growth involve collective cell spreading, which is driven by individual motility and proliferation events within a population of cells. Mathematical models are often used to interpret experimental data and to estimate the parameters so that predictions can be made. Existing methods for parameter estimation typically assume that these parameters are constants and often ignore any uncertainty in the estimated values. We use approximate Bayesian computation (ABC) to estimate the cell diffusivity, D, and the cell proliferation rate, λ, from a discrete model of collective cell spreading, and we quantify the uncertainty associated with these estimates using Bayesian inference. We use a detailed experimental data set describing the collective cell spreading of 3T3 fibroblast cells. The ABC analysis is conducted for different combinations of initial cell densities and experimental times in two separate scenarios: (i) where collective cell spreading is driven by cell motility alone, and (ii) where collective cell spreading is driven by combined cell motility and cell proliferation. We find that D can be estimated precisely, with a small coefficient of variation (CV) of 2–6%. Our results indicate that D appears to depend on the experimental time, which is a feature that has been previously overlooked. Assuming that the values of D are the same in both experimental scenarios, we use the information about D from the first experimental scenario to obtain reasonably precise estimates of λ, with a CV between 4 and 12%. Our estimates of D and λ are consistent with previously reported values; however, our method is based on a straightforward measurement of the position of the leading edge whereas previous approaches have involved expensive cell counting techniques. Additional insights gained using a fully Bayesian approach justify the computational cost, especially since it allows us to accommodate information from different experiments in a principled way.

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We identified the active ingredients in people’s visions of society’s future (“collective futures”) that could drive political behavior in the present. In eight studies (N = 595), people imagined society in 2050 where climate change was mitigated (Study 1), abortion laws relaxed (Study 2), marijuana legalized (Study 3), or the power of different religious groups had increased (Studies 4-8). Participants rated how this future society would differ from today in terms of societal-level dysfunction and development (e.g., crime, inequality, education, technology), people’s character (warmth, competence, morality), and their values (e.g., conservation, self-transcendence). These measures were related to present-day attitudes/intentions that would promote/prevent this future (e.g., act on climate change, vote for a Muslim politician). A projection about benevolence in society (i.e., warmth/morality of people’s character) was the only dimension consistently and uniquely associated with present-day attitudes and intentions across contexts. Implications for social change theories, political communication, and policy design are discussed.

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Due to the numerous possibilities of voicing concerns and the flood of data we are exposed to, local issues are sometimes at risk of being overlooked. This study explores Local Commons, a design intervention in public space that combines situated digital and tangible media in order to engage communities in contributing and debating different perspectives on a given local issue. The intervention invited the community to submit images of their perspectives on the issue, which were displayed on a public screen. Via tangible buttons in front of the screen, community members then agree or disagree on the displayed perspectives, creating a space for deliberation. In a user study, we were specifically interested in testing three aspects of our intervention, which are discussed in this paper: The difference that situatedness, visual content, and tangible interaction can make to urban community engagement.

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The rise of the mobile internet enables the creation of applications that provide new and easier ways for people to organise themselves, raise issues, take action and interact with their city. At the same time, society faces new problems that can only be solved when citizens work together. Nevertheless, a lack of motivation or knowledge often prevents many citizens from regularly contributing to the common good. In this position paper, we present DoGood – a mobile app – as a socio-technological system that aims at supporting the collective intelligence of citizens in their pursuit of civic engagement and civic collaboratories. Our study asks to what extent gamification can motivate users to “do good” deeds. The DoGood app uses gamified elements to encourage citizens to submit and promote their civic activities as well as to join the activities of others. Gamification is sometimes criticised for simply adding a limited number of game elements, such as leaderboards, on top of an existing experience with the hope of increasing motivation. However, in the case of the DoGood app, the process of game design was an integral part of the development, and the gamified elements target the user’s intrinsic motivations instead of providing them with an external reward. In this paper, we present design elements of the app and discuss their potential to support collective intelligence for the common good.

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Language processing is an example of implicit learning of multiple statistical cues that provide probabilistic information regarding word structure and use. Much of the current debate about language embodiment is devoted to how action words are represented in the brain, with motor cortex activity evoked by these words assumed to selectively reflect conceptual content and/or its simulation. We investigated whether motor cortex activity evoked by manual action words (e.g., caress) might reflect sensitivity to probabilistic orthographic-phonological cues to grammatical category embedded within individual words. We first review neuroimaging data demonstrating that nonwords evoke activity much more reliably than action words along the entire motor strip, encompassing regions proposed to be action category specific. Using fMRI, we found that disyllabic words denoting manual actions evoked increased motor cortex activity compared with non-body-part-related words (e.g., canyon), activity which overlaps that evoked by observing and executing hand movements. This result is typically interpreted in support of language embodiment. Crucially, we also found that disyllabic nonwords containing endings with probabilistic cues predictive of verb status (e.g., -eve) evoked increased activity compared with nonwords with endings predictive of noun status (e.g., -age) in the identical motor area. Thus, motor cortex responses to action words cannot be assumed to selectively reflect conceptual content and/or its simulation. Our results clearly demonstrate motor cortex activity reflects implicit processing of ortho-phonological statistical regularities that help to distinguish a word's grammatical class.

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Classic identity negative priming (NP) refers to the finding that when an object is ignored, subsequent naming responses to it are slower than when it has not been previously ignored (Tipper, S.P., 1985. The negative priming effect: inhibitory priming by ignored objects. Q. J. Exp. Psychol. 37A, 571-590). It is unclear whether this phenomenon arises due to the involvement of abstract semantic representations that the ignored object accesses automatically. Contemporary connectionist models propose a key role for the anterior temporal cortex in the representation of abstract semantic knowledge (e.g., McClelland, J.L., Rogers, T.T., 2003. The parallel distributed processing approach to semantic cognition. Nat. Rev. Neurosci. 4, 310-322), suggesting that this region should be involved during performance of the classic identity NP task if it involves semantic access. Using high-field (4 T) event-related functional magnetic resonance imaging, we observed increased BOLD responses in the left anterolateral temporal cortex including the temporal pole that was directly related to the magnitude of each individual's NP effect, supporting a semantic locus. Additional signal increases were observed in the supplementary eye fields (SEF) and left inferior parietal lobule (IPL).

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Studies of delayed nonmatching-to-sample (DNMS) performance following lesions of the monkey cortex have revealed a critical circuit of brain regions involved in forming memories and retaining and retrieving stimulus representations. Using event-related functional magnetic resonance imaging (fMRI), we measured brain activity in 10 healthy human participants during performance of a trial-unique visual DNMS task using novel barcode stimuli. The event-related design enabled the identification of activity during the different phases of the task (encoding, retention, and retrieval). Several brain regions identified by monkey studies as being important for successful DNMS performance showed selective activity during the different phases, including the mediodorsal thalamic nucleus (encoding), ventrolateral prefrontal cortex (retention), and perirhinal cortex (retrieval). Regions showing sustained activity within trials included the ventromedial and dorsal prefrontal cortices and occipital cortex. The present study shows the utility of investigating performance on tasks derived from animal models to assist in the identification of brain regions involved in human recognition memory.

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Recent models of language comprehension have assumed a tight coupling between the semantic representations of action words and cortical motor areas. We combined functional MRI with cytoarchitectonically defined probabilistic maps of left hemisphere primary and premotor cortices to analyse responses of functionally delineated execution- and observation-related regions during comprehension of action word meanings associated with specific effectors (e.g., punch, bite or stomp) and processing of items with various levels of lexical information (non body part-related meanings, nonwords, and visual character strings). The comprehension of effector specific action word meanings did not elicit preferential activity corresponding to the somatotopic organisation of effectors in either primary or premotor cortex. However, generic action word meanings did show increased BOLD signal responses compared to all other classes of lexical stimuli in the pre-SMA. As expected, the majority of the BOLD responses elicited by the lexical stimuli were in association cortex adjacent to the motor areas. We contrast our results with those of previous studies reporting significant effects for only 1 or 2 effectors outside cytoarchitectonically defined motor regions and discuss the importance of controlling for potentially confounding lexical variables such as imageability. We conclude that there is no strong evidence for a somatotopic organisation of action word meaning representations and argue the pre-SMA might have a role in maintaining abstract representations of action words as instructional cues.

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This research describes some of the salient features of Indigenous ways of working with multimodal literacies in digital contexts of use that emerged within an Indigenous school community with the oversight of Aboriginal Elders. This is significant because the use of multimodal literacy practices among a growing number of Indigenous school community groups has not been an emphasis of multimodal literacy research to date. Furthermore, authentic examples of Indigenous multimodal texts are often difficult to locate within Euro-centric educational systems of postcolonial countries. The research was conducted over a full year with students from middle and upper primary (aged 8.5–12.5 years) in an Indigenous Independent school in South-East Queensland, Australia. The project applied participatory research methods in which the research agenda was negotiated with the cultural community. Indigenous ways of multimodal literacy practices emerged as transgenerational, multimodal, placed, and collective. The findings have implications for teachers and researchers to re-envisage Indigenous ways of multimodal literacy practices in the digital age.