833 resultados para Local Learning and Employment Network (LLENs)


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Successful motor performance requires the ability to adapt motor commands to task dynamics. A central question in movement neuroscience is how these dynamics are represented. Although it is widely assumed that dynamics (e.g., force fields) are represented in intrinsic, joint-based coordinates (Shadmehr R, Mussa-Ivaldi FA. J Neurosci 14: 3208-3224, 1994), recent evidence has questioned this proposal. Here we reexamine the representation of dynamics in two experiments. By testing generalization following changes in shoulder, elbow, or wrist configurations, the first experiment tested for extrinsic, intrinsic, or object-centered representations. No single coordinate frame accounted for the pattern of generalization. Rather, generalization patterns were better accounted for by a mixture of representations or by models that assumed local learning and graded, decaying generalization. A second experiment, in which we replicated the design of an influential study that had suggested encoding in intrinsic coordinates (Shadmehr and Mussa-Ivaldi 1994), yielded similar results. That is, we could not find evidence that dynamics are represented in a single coordinate system. Taken together, our experiments suggest that internal models do not employ a single coordinate system when generalizing and may well be represented as a mixture of coordinate systems, as a single system with local learning, or both.

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Organizations of the Social Economy in Spain accounted for 13% of employment and 12% of GDP in 2013, according to the Spanish Confederation fo Social Economy. Also, according to various institutions and studies, the role of Social Economy has become relevant due to they represent a model promoting the creation of collective business projects with greater sustainability and potential than models of individual self-employment. However, despite all this, there are few academic studies or sectoral reports analyzing employment in this sector, especially in the case of youth employment. This study aims to fill this gap in the literature analyzing the scared available data in order to show the numbers and characteristics of youth employment in this sector. Results show the weight of youth employment in the Social Economy is higher than the economy overall.

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Current literature warns organisations about a global ageing phenomenon. Workplace ageing is causing a diminishing work pool which has consequences for a sustainable workforce in the future. This phenomenon continues to impact on local government councils in Australia. Australia has one of the world’s most rapidly ageing populations, and there is evidence that Australian local government councils are already resulting in an unsustainable workforce. Consequently, this research program investigated the role of older workers in the Queensland local government workplace in enabling them to extend their working lives towards transitional employment and a sustainable workforce in the future. Transitional Employment is intended as a strategy for enabling individuals to have greater control over their employment options and their employability during the period leading to their final exit from the workforce. There was no evidence of corporate support for older workers in Queensland local government councils other than tokenistic government campaigns encouraging organisations to "better value their older workers". (Queensland Government, 2007d, p.6). TE is investigated as a possible intervention for older workers in the future. The international and national literature review reflected a range of matters impacting on current older workers in the workforce and barriers preventing them from accessing services towards extending their employment beyond the traditional retirement age (60 years) as defined by the Australian Government; an age when individuals can access their superannuation. Learning and development services were identified as one of those barriers. There was little evidence of investment in or consistent approaches to supporting older workers by organisations. Learning and development services appeared at best to be ad hoc, reactive to corporate productivity and outputs with little recognition of the ageing phenomenon (OECD, 2006, p.23) and looming skills and labour shortages (ALGA, 2006, p. 19). Themes from the literature review led to the establishment of three key research questions: 1. What are the current local government workforce issues impacting on skills and labour retention? 2. What are perceptions about the current workplace environment? And, 3. What are the expectations about learning and development towards extending employability of older workers within the local government sector? The research questions were explored by utilising three qualitative empirical studies, using some numerical data for reporting and comparative analysis. Empirical Study One investigated common themes for accessing transitional employment and comprised two phases. A literature review and Study One data analysis enabled the construction of an initial Transitional Employment Model which includes most frequent themes. Empirical Study Two comprised focus groups to further consider those themes. This led to identification of issues impacting the most on access to learning and development by older workers and towards a revised TEM. Findings presented majority support for transitional employment as a strategy for supporting older workers to work beyond their traditional retirement age. Those findings are presented as significant issues impacting on access to transitional employment within the final 3-dimensionsal TEM. The model is intended as a guide for responding to an ageing workforce by local government councils in the future. This study argued for increased and improved corporate support, particularly for learning and development services for older workers. Such support will enable older workers to maintain their employability and extend their working lives; a sustainable workforce in the future.

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The higher education sector is under ongoing pressure to demonstrate quality and efficacy of educational provision, including graduate outcomes. Preparing students as far as possible for the world of professional work has become one of the central tasks of contemporary universities. This challenging task continues to receive significant attention by policy makers and scholars, in the broader contexts of widespread labour market uncertainty and massification of the higher education system (Tomlinson, 2012). In contrast to the previous era of the university, in which ongoing professional employment was virtually guaranteed to university-qualified individuals, contemporary graduates must now be proactive and flexible. They must adapt to a job market that may not accept them immediately, and has continually shifting requirements (Clarke, 2008). The saying goes that rather than seeking security in employment, graduates must now “seek security in employability”. However, as I will argue in this chapter, the current curricular and pedagogic approaches universities adopt, and indeed the core structural characteristics of university-based education, militate against the development of the capabilities that graduates require now and into the future.

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This article introduces a new neural network architecture, called ARTMAP, that autonomously learns to classify arbitrarily many, arbitrarily ordered vectors into recognition categories based on predictive success. This supervised learning system is built up from a pair of Adaptive Resonance Theory modules (ARTa and ARTb) that are capable of self-organizing stable recognition categories in response to arbitrary sequences of input patterns. During training trials, the ARTa module receives a stream {a^(p)} of input patterns, and ARTb receives a stream {b^(p)} of input patterns, where b^(p) is the correct prediction given a^(p). These ART modules are linked by an associative learning network and an internal controller that ensures autonomous system operation in real time. During test trials, the remaining patterns a^(p) are presented without b^(p), and their predictions at ARTb are compared with b^(p). Tested on a benchmark machine learning database in both on-line and off-line simulations, the ARTMAP system learns orders of magnitude more quickly, efficiently, and accurately than alternative algorithms, and achieves 100% accuracy after training on less than half the input patterns in the database. It achieves these properties by using an internal controller that conjointly maximizes predictive generalization and minimizes predictive error by linking predictive success to category size on a trial-by-trial basis, using only local operations. This computation increases the vigilance parameter ρa of ARTa by the minimal amount needed to correct a predictive error at ARTb· Parameter ρa calibrates the minimum confidence that ARTa must have in a category, or hypothesis, activated by an input a^(p) in order for ARTa to accept that category, rather than search for a better one through an automatically controlled process of hypothesis testing. Parameter ρa is compared with the degree of match between a^(p) and the top-down learned expectation, or prototype, that is read-out subsequent to activation of an ARTa category. Search occurs if the degree of match is less than ρa. ARTMAP is hereby a type of self-organizing expert system that calibrates the selectivity of its hypotheses based upon predictive success. As a result, rare but important events can be quickly and sharply distinguished even if they are similar to frequent events with different consequences. Between input trials ρa relaxes to a baseline vigilance pa When ρa is large, the system runs in a conservative mode, wherein predictions are made only if the system is confident of the outcome. Very few false-alarm errors then occur at any stage of learning, yet the system reaches asymptote with no loss of speed. Because ARTMAP learning is self stabilizing, it can continue learning one or more databases, without degrading its corpus of memories, until its full memory capacity is utilized.

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This article investigates work related learning and development amongst mature aged workers from a lifespan developmental psychology perspective. The current study follows on from research regarding the construction and revision of the Learning and Development Survey (LDS; Tones & Pillay, 2008). Designed to measure adaptive development for work related learning, the revised LDS (R-LDS) encompasses goal selection, engagement and disengagement from individual and organisational perspectives. Previous survey findings from a mixed age sample of local government workers suggest that mature aged workers aged over 45 years are less likely to report engagement in learning and development goals than younger workers, which is partly due to insufficient opportunities at work. In the current paper, exploratory factor analysis was used to investigate responses to the R-LDS amongst two groups of mature aged workers from a local government (LG) and private healthcare (PH) organisation to determine the stability of the R-LDS. Organisational constraints to development accounted for almost a quarter of the variance in R-LDS scores for both samples, while remaining factors emerged in different orders for each data set. Organisational opportunities for development explained about 17% of the variance in R-LDS scores in the LG sample, while the individual goal disengagement factor contributed a comparable proportion of variance to R-LDS scores for the PH sample. Findings from the current study indicate that opportunities for learning and development at work may be age structured and biased towards younger workers. Implications for professional practice are discussed and focus on improving the engagement of mature aged workers.

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Youth population is increasing explosively particularly in developing countries as a result of rapid urbanization. This increase is bringing large number of social and economic problems. For instance the impacts of job and training availability, and the physical, social and cultural quality of urban environment on young people are enormous, and affect their health, lifestyles, and well-being (Gleeson and Sipe 2006). Besides this, globalization and technological developments are affecting youth in urban areas in all parts of the world, both positively and negatively (Robertson 1995). The rapidly advancing information and communications technologies (ICTs) helps in addressing social and economic problems caused by the rapid growth of urban youth populations in developing countries. ICTs offer opportunities to young people for learning, skill development and employment. But there are downsides: young people in many developing countries lack of having broad access to these new technologies, they are vulnerable to global market changes, and ICTs link them into global cultures which promote consumer goods, potentially eroding local cultures and community values (Manacorda and Petrongolo 1999). However we believe that the positives outweigh such negatives. At the beginning of the twenty-first century, the world’s young population number more than they ever have. There are over a billion young people between the ages of 15 and 24, which 85 per cent of them live in developing countries and mainly in urban environments. Many of these young people are in the process of making, or have already made, the transition from school to work. During the last two decades all around the world, these young people, as new workers, have faced a number of challenges associated with globalization and technological advances on labour markets (United Nations 2004). The continuous decrease in the manufacturing employment is made many of the young people facing three options: getting jobs in the informal economy with insecurity and poor wages and working conditions, or getting jobs in the low-tier service industries, or developing their vocational skills to benefit from new opportunities in the professional and advanced technical/knowledge sectors. Moreover in developing countries a large portion of young people are not even lucky enough to choose among any of these options, and consequently facing long-term unemployment, which makes them highly vulnerable. The United Nations’ World Youth Employment report (2004) indicates that in almost all countries, females tend to be far more vulnerable than males in terms of long-term unemployment, and young people who have advanced qualifications are far less likely to experience long-term unemployment than others. In the limited opportunities of the formal labour market, those with limited vocational skills resort to forced entrepreneurship and selfemployment in the informal economy, often working for low pay under hazardous conditions, with only few prospects for the future (United Nations 2005a). The International Labour Organization’s research (2004) revealed that the labour force participation rates for young people decreased by almost four per cent (which is equivalent of 88 million young people) between 1993 and 2003. This is largely as a result of the increased number of young people attending school, high overall unemployment rates, and the fact that some young people gave up any hope of finding work and dropped out of the labour market. At the regional level, youth unemployment was highest in Middle East and North Africa (MENA) (25.6%) and sub-Saharan Africa (21%) and lowest in East Asia (7%) and the industrialized economies(13.4%) (International Labour Organization 2004). The youth in economically disadvantaged regions (e.g. the MENA region) face many challenges in education and training that delivers them the right set of skills and knowledge demanded by the labour market. As a consequence, the transition from school to work is mostly unsuccessful and young population end up either unemployed or underemployed in the informal sectors (United Nations 2005b). Unemployment and lack of economic prospects of the urban youth are pushing many of them into criminal acts, excessive alcohol use, substance addiction, and also in many cases resulting in processes of social or political violence (Fernandez-Maldonado 2004; United Nations 2005a). Long-term unemployment leads young people in a process of marginalisation and social exclusion (United Nations 2004). The sustained high rates of long-term youth unemployment have a number of negative effects on societies. First, it results in countries failing to take advantage of the human resources to increase their productive potential, at a time of transition to a globalized world that inexorably demands such leaps in productive capacity. Second, it reinforces the intergenerational transmission of poverty. Third, owing to the discrepancy between more education and exposure to the mass media and fewer employment opportunities, it may encourage the spread of disruptive behaviours, recourse to illegal alternatives for generating income and the loss of basic societal values, all of which erode public safety and social capital. Fourth, it may trigger violent and intractable political conflicts. And lastly, it may exacerbate intergenerational conflicts when young people perceive a lack of opportunity and meritocracy in a system that favours adults who have less formal education and training but more wealth, power and job stability (Hopenhayn 2002). To assist in addressing youth’s skill training and employment problems this paper scrutinises useful international practices, policies, initiatives and programs targeting youth skill training, particularly in ICTs. The MENA national governments and local authorities could consider implementing similar initiative and strategies to address some of the youth employment issues. The broader aim of this paper is to investigate the successful practice and strategies for the information and communication related income generation opportunities for young people to: promote youth entrepreneurship; promote public-private partnerships; target vulnerable groups of young people; narrow digital divide; and put young people in charge. The rest of this paper is organised in five parts. First, the paper provides an overview of the literature on the knowledge economy, skill, education and training issues. Secondly, it reviews the role of ICTs for vocational skill development and employability. Thirdly, it discusses the issues surrounding the development of the digital divide. Fourthly, the paper underlines types and the importance of developing ICT initiatives targeting young people, and reviews some of the successful policy implementations on ICT-based initiatives from both developed and developing countries that offer opportunities to young people for learning, skill development and employment. Then the paper concludes by providing useful generalised recommendations for the MENA region countries and cities in: advocating possible opportunities for ICT generated employment for young people; and discussing how ICT policies could be modified and adopted to meet young people’s needs.

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Training that is relevant to employers is not necessarily enriching for employees, especially those on the lower salary scales. The authors argue that the analysis of training and development needs to be understood in the context of the employment relationship. Drawing on reasearch evidence from six case studies in the public sector, the article examines the impact of changes in work organisation on workplace learning, managers' and employees' own strategies towards it and the limitations of tools such as appraisal. Since employees' existing qualifications are poorly utilised and their development needs often frustrated, issues concerning job design, occupational progression routes and employee entitlements need to be addressed

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This paper introduces ART-EMAP, a neural architecture that uses spatial and temporal evidence accumulation to extend the capabilities of fuzzy ARTMAP. ART-EMAP combines supervised and unsupervised learning and a medium-term memory process to accomplish stable pattern category recognition in a noisy input environment. The ART-EMAP system features (i) distributed pattern registration at a view category field; (ii) a decision criterion for mapping between view and object categories which can delay categorization of ambiguous objects and trigger an evidence accumulation process when faced with a low confidence prediction; (iii) a process that accumulates evidence at a medium-term memory (MTM) field; and (iv) an unsupervised learning algorithm to fine-tune performance after a limited initial period of supervised network training. ART-EMAP dynamics are illustrated with a benchmark simulation example. Applications include 3-D object recognition from a series of ambiguous 2-D views.

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A neural model is described of how adaptively timed reinforcement learning occurs. The adaptive timing circuit is suggested to exist in the hippocampus, and to involve convergence of dentate granule cells on CA3 pyramidal cells, and NMDA receptors. This circuit forms part of a model neural system for the coordinated control of recognition learning, reinforcement learning, and motor learning, whose properties clarify how an animal can learn to acquire a delayed reward. Behavioral and neural data are summarized in support of each processing stage of the system. The relevant anatomical sites are in thalamus, neocortex, hippocampus, hypothalamus, amygdala, and cerebellum. Cerebellar influences on motor learning are distinguished from hippocampal influences on adaptive timing of reinforcement learning. The model simulates how damage to the hippocampal formation disrupts adaptive timing, eliminates attentional blocking, and causes symptoms of medial temporal amnesia. It suggests how normal acquisition of subcortical emotional conditioning can occur after cortical ablation, even though extinction of emotional conditioning is retarded by cortical ablation. The model simulates how increasing the duration of an unconditioned stimulus increases the amplitude of emotional conditioning, but does not change adaptive timing; and how an increase in the intensity of a conditioned stimulus "speeds up the clock", but an increase in the intensity of an unconditioned stimulus does not. Computer simulations of the model fit parametric conditioning data, including a Weber law property and an inverted U property. Both primary and secondary adaptively timed conditioning are simulated, as are data concerning conditioning using multiple interstimulus intervals (ISIs), gradually or abruptly changing ISis, partial reinforcement, and multiple stimuli that lead to time-averaging of responses. Neurobiologically testable predictions are made to facilitate further tests of the model.