Mother-Infant Reciprocity and the Development of Joint Attention in 12 Month Old Infants

Social contingency is the ability to connect social stimuli, such as those behaviors performed by oneself and those performed by others. Detecting social contingencies occurs by means of reciprocity through shared experiences with others. Reciprocity denotes a circumstance in which two individuals participate in a collaborative exchange, and is distinguished from an event in which two individuals engage in separate, unrelated activities. Specifically, reciprocity incorporates joint attention (JA), which occurs when two individuals simultaneously and visually attend to the same item. JA is facilitated by gazing and pointing, whereby one individual initiates the action and the second individual follows suit by, for example, gaze-following. However, little is known about the role the mother may play in the development of JA. The purpose of our study was to investigate social contingency between mothers and infants engaging in dyadic interactions. Thirty-three 12-month-old typically developing infants (M = 12.2, SD = .19; N = 19 males) were filmed for 10 minutes during free play with their mothers and toys provided by an experimenter. Reciprocity was measured by coding mother-infant interactions when a precise chain of events occurred: (1) mother initiated a bid by introducing a toy/activity or request to the infant, (2) infant accepted the bid/request by engaging in play with the given toy/activity, and (3) mother persisted by continuing to engage in play with said toy/activity. We computed a Pearson Correlation to assess the relation between the mothers’ initiations of JA and their infants’ responses to JA. We found a moderately positive correlation between the two variables (r= 0.37, p<.05). Our findings suggest that reciprocity, an important component of social relationships, during parent-infant dyads may serve as a scaffold for joint attention abilities, which have been linked to social and language development.

Motivating residents to combat invasive species on private lands: social norms and community reciprocity

Invasive species (IS) threaten biodiversity and ecosystem functioning. To achieve landscape-scale reductions in IS and the associated gains for biodiversity, IS control efforts must be expanded across private lands. Enhancing IS control across private lands requires an understanding of the factors that motivate residents to engage or prohibit residents from engaging in efforts to control IS. Drawing from the collective interest model and literature, we sought to understand how a wide range of interpersonal, intrapersonal, and contextual factors might influence resident action around combating the invasive tree albizia (Falcataria moluccana), in the Puna District of Hawaiʻi. To do so, we used a cross-sectional survey of 243 residents and elastic net regression techniques. We found that residents’ actions related to IS control were related to their perceptions of social norms and community reciprocity regarding albizia control, as well as their knowledge of effective control strategies and their risk perceptions regarding albizia. These findings suggest that, although common intervention approaches that focus on providing education or subsidies are important, they may be more effective at reducing the spread of IS if coupled with approaches that build community reciprocity and norms.

The Descent of Pluto: Interactive dynamics, specialisation and reciprocity of roles in a Wikipedia debate

International audience

A study of employee affective organisational commitment and retention in Pakistan:the roles of psychological contract breach and norms of reciprocity

Social exchange theory and notions of reciprocity have long been assumed to explain the relationship between psychological contract breach and important employee outcomes. To date, however, there has been no explicit testing of these assumptions. This research, therefore, explores the mediating role of negative, generalized, and balanced reciprocity, in the relationships between psychological contract breach and employees’ affective organizational commitment and turnover intentions. A survey of 247 Pakistani employees of a large public university was analyzed using structural equation modeling and bootstrapping techniques, and provided excellent support for our model. As predicted, psychological contract breach was positively related to negative reciprocity norms and negatively related to generalized and balanced reciprocity norms. Negative and generalized (but not balanced) reciprocity were negatively and positively (respectively) related to employees’ affective organizational commitment and fully mediated the relationship between psychological contract breach and affective organizational commitment. Moreover, affective organizational commitment fully mediated the relationship between generalized and negative reciprocity and employees’ turnover intentions. Implications for theory and practice are discussed.

Being There

This 60 minute work looked to challenge traditional expectations of how dancers ‘perform’ and what it means when they are ‘themselves’ onstage. The audience was asked to sit in an ellipse on stage and the dancers were often performing quite close to them. While the audience didn’t move once the work began, the proximity to the dancers allowed them an unusual opportunity to see these dancers deconstructing their own profession and their own world of performance in an intimate environment. This was done for, and with the audience, and for some, it connected them deeply with the performers. For Georg Simmel, an early 20th Century sociologist, ‘the eye of a person discloses his own soul when he seeks to uncover that of another. What occurs in this direct mutual reciprocity is the entire field of human relationships.’ Performer authenticity, while utilised often in film and theatre, is not common in the form of dance. Because of our societal tendency toward the desire for authenticity, and its uncommon usage in dance, an inversion of this convention is one of the many tools that is available to choreographers to form deep connections with their audience and is one that is gaining popularity throughout the world as a form of connection via reality and the immediacy of live performance.

A new look at leadership in collaborative networks : process catalysts

Collaborative networks have come to form a large part of the public sector’s strategy to address ongoing and often complex social problems. The relational power of networks, with its emphasis on trust, reciprocity and mutuality provides the mechanism to integrate previously dispersed and even competitive entities into a collective venture(Agranoff 2003; Agranoff and McGuire 2003; Mandell 1994; Mandell and Harrington 1999). It is argued that the refocusing of a single body of effort to a collective contributes to reducing duplication and overlap of services, maximizes increasingly scarce resources and contributes to solving intractable or 'wicked’problems (Clarke and Stewart 1997). Given the current proliferation of collaborative networks and the fact that they are likely to continue for some time, concerns with the management and leadership of such arrangements for optimal outcomes are increasingly relevant. This is especially important for public sector managers who are used to working in a top-down, hierarchical manner. While the management of networks (Agranoff and McGuire 2001, 2003), including collaborative or complex networks (Kickert et al. 1997; Koppenjan and Klijn 2004), has been the subject of considerable attention, there has been much less explicit discussion on leadership approaches in this context. It is argued in this chapter that the traditional use of the terms ‘leader’ or ‘leadership’ does not apply to collaborative networks. There are no ‘followers’ in collaborative networks or supervisor-subordinate relations. Instead there are equal, horizontal relationships that are focused on delivering systems change. In this way the emergent organizational forms such as collaborative networks challenge older models of leadership. However despite the questionable relevance of old leadership styles to the contemporary work environment, no clear alternative has come along to take its place.

Stochastic modelling of financial time series with memory and multifractal scaling

Financial processes may possess long memory and their probability densities may display heavy tails. Many models have been developed to deal with this tail behaviour, which reflects the jumps in the sample paths. On the other hand, the presence of long memory, which contradicts the efficient market hypothesis, is still an issue for further debates. These difficulties present challenges with the problems of memory detection and modelling the co-presence of long memory and heavy tails. This PhD project aims to respond to these challenges. The first part aims to detect memory in a large number of financial time series on stock prices and exchange rates using their scaling properties. Since financial time series often exhibit stochastic trends, a common form of nonstationarity, strong trends in the data can lead to false detection of memory. We will take advantage of a technique known as multifractal detrended fluctuation analysis (MF-DFA) that can systematically eliminate trends of different orders. This method is based on the identification of scaling of the q-th-order moments and is a generalisation of the standard detrended fluctuation analysis (DFA) which uses only the second moment; that is, q = 2. We also consider the rescaled range R/S analysis and the periodogram method to detect memory in financial time series and compare their results with the MF-DFA. An interesting finding is that short memory is detected for stock prices of the American Stock Exchange (AMEX) and long memory is found present in the time series of two exchange rates, namely the French franc and the Deutsche mark. Electricity price series of the five states of Australia are also found to possess long memory. For these electricity price series, heavy tails are also pronounced in their probability densities. The second part of the thesis develops models to represent short-memory and longmemory financial processes as detected in Part I. These models take the form of continuous-time AR(∞) -type equations whose kernel is the Laplace transform of a finite Borel measure. By imposing appropriate conditions on this measure, short memory or long memory in the dynamics of the solution will result. A specific form of the models, which has a good MA(∞) -type representation, is presented for the short memory case. Parameter estimation of this type of models is performed via least squares, and the models are applied to the stock prices in the AMEX, which have been established in Part I to possess short memory. By selecting the kernel in the continuous-time AR(∞) -type equations to have the form of Riemann-Liouville fractional derivative, we obtain a fractional stochastic differential equation driven by Brownian motion. This type of equations is used to represent financial processes with long memory, whose dynamics is described by the fractional derivative in the equation. These models are estimated via quasi-likelihood, namely via a continuoustime version of the Gauss-Whittle method. The models are applied to the exchange rates and the electricity prices of Part I with the aim of confirming their possible long-range dependence established by MF-DFA. The third part of the thesis provides an application of the results established in Parts I and II to characterise and classify financial markets. We will pay attention to the New York Stock Exchange (NYSE), the American Stock Exchange (AMEX), the NASDAQ Stock Exchange (NASDAQ) and the Toronto Stock Exchange (TSX). The parameters from MF-DFA and those of the short-memory AR(∞) -type models will be employed in this classification. We propose the Fisher discriminant algorithm to find a classifier in the two and three-dimensional spaces of data sets and then provide cross-validation to verify discriminant accuracies. This classification is useful for understanding and predicting the behaviour of different processes within the same market. The fourth part of the thesis investigates the heavy-tailed behaviour of financial processes which may also possess long memory. We consider fractional stochastic differential equations driven by stable noise to model financial processes such as electricity prices. The long memory of electricity prices is represented by a fractional derivative, while the stable noise input models their non-Gaussianity via the tails of their probability density. A method using the empirical densities and MF-DFA will be provided to estimate all the parameters of the model and simulate sample paths of the equation. The method is then applied to analyse daily spot prices for five states of Australia. Comparison with the results obtained from the R/S analysis, periodogram method and MF-DFA are provided. The results from fractional SDEs agree with those from MF-DFA, which are based on multifractal scaling, while those from the periodograms, which are based on the second order, seem to underestimate the long memory dynamics of the process. This highlights the need and usefulness of fractal methods in modelling non-Gaussian financial processes with long memory.

An analytical method to solve a general class of nonlinear reactive transport models

Three recent papers published in Chemical Engineering Journal studied the solution of a model of diffusion and nonlinear reaction using three different methods. Two of these studies obtained series solutions using specialized mathematical methods, known as the Adomian decomposition method and the homotopy analysis method. Subsequently it was shown that the solution of the same particular model could be written in terms of a transcendental function called Gauss’ hypergeometric function. These three previous approaches focused on one particular reactive transport model. This particular model ignored advective transport and considered one specific reaction term only. Here we generalize these previous approaches and develop an exact analytical solution for a general class of steady state reactive transport models that incorporate (i) combined advective and diffusive transport, and (ii) any sufficiently differentiable reaction term R(C). The new solution is a convergent Maclaurin series. The Maclaurin series solution can be derived without any specialized mathematical methods nor does it necessarily involve the computation of any transcendental function. Applying the Maclaurin series solution to certain case studies shows that the previously published solutions are particular cases of the more general solution outlined here. We also demonstrate the accuracy of the Maclaurin series solution by comparing with numerical solutions for particular cases.

An integrated framework to assess financial reward systems in construction projects

Motivation is a major driver of project performance. Despite team member ability to deliver successful project outcomes if they are not positively motivated to pursue joint project goals, then performance will be constrained. One approach to improving the motivation of project organizations is by offering a financial reward for the achievement of set performance standards above a minimum required level. However, little investigation has been undertaken into the features of successful incentive systems as a part of an overall delivery strategy. With input from organizational management literature, and drawing on the literature covering psychological and economic theories of motivation, this paper presents an integrated framework that can be used by project organizations to assess the impact of financial reward systems on motivation in construction projects. The integrated framework offers four motivation indicators which reflect key theoretical concepts across both psychological and economic disciplines. The indicators are: (1) Goal Commitment, (2) Distributive Justice, (3) Procedural Justice, and (4) Reciprocity. The paper also interprets the integrated framework against the results of a successful Australian social infrastructure project case study and identifies key learning’s for project organizations to consider when designing financial reward systems. Case study results suggest that motivation directed towards the achievement of incentive goals is influenced not only by the value placed on the financial reward for commercial benefit, but also driven by the strength of the project initiatives that encourage just and fair dealings, supporting the establishment of trust and positive reciprocal behavior across a project team. The strength of the project relationships was found to be influenced by how attractive the achievement of the goal is to the incentive recipient and how likely they were to push for the achievement of the goal. Interestingly, findings also suggested that contractor motivation is also influenced by the fairness of the performance measurement process and their perception of the trustworthiness and transparency of their client. These findings provide the basis for future research on the impact of financial reward systems on motivation in construction projects. It is anticipated that such research will shed new light on this complex topic and further define how reward systems should be designed to promote project team motivation. Due to the unique nature of construction projects with high levels of task complexity and interdependence, results are expected to vary in comparison to previous studies based on individuals or single-entity organizations.

Good Practice Report : Blended Learning

In early 2011, the Australian Learning and Teaching Council Ltd (ALTC) commissioned a series of Good Practice Reports on completed ALTC projects and fellowships. This report will: • Provide a summative evaluation of the good practices and key outcomes for teaching and learning from completed ALTC projects and fellowships relating to blended learning • Include a literature review of the good practices and key outcomes for teaching and learning from national and international research • Identify areas in which further work or development are appropriate. The literature abounds with definitions; it can be argued that the various definitions incorporate different perspectives, but there is no single, collectively accepted definition. Blended learning courses in higher education can be placed somewhere on a continuum, between fully online and fully face-to-face courses. Consideration must therefore be given to the different definitions for blended learning presented in the literature and by users and stakeholders. The application of this term in these various projects and fellowships is dependent on the particular focus of the team and the conditions and situations under investigation. One of the key challenges for projects wishing to develop good practice in blended learning is the lack of a universally accepted definition. The findings from these projects and fellowships reveal the potential of blended learning programs to improve both student outcomes and levels of satisfaction. It is clear that this environment can help teaching and learning engage students more effectively and allow greater participation than traditional models. Just as there are many definitions, there are many models and frameworks that can be successfully applied to the design and implementation of such courses. Each academic discipline has different learning objectives and in consequence there can’t be only one correct approach. This is illustrated by the diversity of definitions and applications in the ALTC funded projects and fellowships. A review of the literature found no universally accepted guidelines for good practice in higher education. To inform this evaluation and literature review, the Seven Principles for Good Practice in Undergraduate Education, as outlined by Chickering and Gamson (1987), were adopted: 1. encourages contacts between students and faculty 2. develops reciprocity and cooperation among students 3. uses active learning techniques 4. gives prompt feedback 5. emphasises time on task 6. communicates high expectations 7. respects diverse talents and ways of learning. These blended learning projects have produced a wide range of resources that can be used in many and varied settings. These resources include: books, DVDs, online repositories, pedagogical frameworks, teaching modules. In addition there is valuable information contained in the published research data and literature reviews that inform good practice and can assist in the development of courses that can enrich and improve teaching and learning.

Evolving a relationship for cross-cultural participatory innovation

Participatory design prioritises the agency of those who will be most affected by design outcomes. However in cross cultural innovation involving indigenous and non-indigenous communities there is much work to do to develop the cross cultural innovation practices that can best bring together different skills, perspectives and ways of knowing in order to realise the aspirations of indigenous peoples. In this short paper we outline a work-inprogress method based upon relationship development and reciprocity over practical, tangible and culturally appropriate activities. We argue that in a cross-cultural setting the participatory innovation process must be part of a larger relationship building process. The paper centres around a proposed design project with a remote indigenous community on the Groote Eylandt archipelago. A project proposal has evolved from a relationship built through ecological work between scientists and the local community to study native populations of animal species. We describe the context and history and our proposed approach to engaging indigenous knowledge in design.