A Collaborative Approach for Online Dementia Care Training

There are obvious benefits to working in collaboration. However, real collaboration takes time; time to engage in meetings, complete accountability processes, and resolve problems. The delicate balance between democracy and efficiency can be compromised when you have to choose between equal participation and looming deadlines (Stoecker, 2003). Weaver and Cousins (2004) described this dilemma as assessing manageability or having to make a choice between achieving complete diversity on the researcher-community team and the unwieldiness of working with a large committee. Compromise is often necessary. This article describes our experiences using a collaborative approach involving university-based researchers and community professionals—in this case, long-term care (LTC) managers, administrators, and hospital-based educators and researchers—to create an online dementia care training program.

A Collaborative Approach for Online Dementia Care Training

There are obvious benefits to working in collaboration. However, real collaboration takes time; time to engage in meetings, complete accountability processes, and resolve problems. The delicate balance between democracy and efficiency can be compromised when you have to choose between equal participation and looming deadlines (Stoecker, 2003). Weaver and Cousins (2004) described this dilemma as assessing manageability or having to make a choice between achieving complete diversity on the researcher-community team and the unwieldiness of working with a large committee. Compromise is often necessary. This article describes our experiences using a collaborative approach involving university-based researchers and community professionals—in this case, long-term care (LTC) managers, administrators, and hospital-based educators and researchers—to create an online dementia care training program.

A Large Committee Machine Learning Noisy Rules

Statistical mechanics is used to study generalization in a tree committee machine with K hidden units and continuous weights trained on examples generated by a teacher of the same structure but corrupted by noise. The corruption is due to additive gaussian noise applied in the input layer or the hidden layer of the teacher. In the large K limit the generalization error εg as function of α, the number of patterns per adjustable parameter, shows a qualitatively similar behavior for the two cases: It does not approach its optimal value and is nonmonotonic if training is done at zero temperature. This remains true even when replica symmetry breaking is taken into account. Training at a fixed positive temperature leads, within the replica symmetric theory, to an α-k decay of εg toward its optimal value. The value of k is calculated and found to depend on the model of noise. By scaling the temperature with α, the value of k can be increased to an optimal value kopt. However, at one step of replica symmetry breaking at a fixed positive temperature εg decays as α−kopt. So, although εg will approach its optimal value with increasing sample size for any fixed K, the convergence is only uniform in K when training at a positive temperature.

LEARNING AND GENERALIZATION THEORIES OF LARGE COMMITTEE-MACHINES

The study of the distribution of volumes associated to the internal representations of learning examples allows us to derive the critical learning capacity [Formula: see text] of large committee machines, to verify the stability of the solution in the limit of a large number K of hidden units and to find a Bayesian generalization cross-over at a=K.

Unesco and African Historiography

Unesco's General History of Africa (henceforth GHA) is now nearing completion—seven out of the eight volumes having been published in English, at least—and the time is ripe to draw attention to its role in the historiography of African history, a role very different from that played by the Cambridge History of Africa with which it is often compared. In certain ways the Unesco project has been a unique venture, and not just in African history but, in general, because it broke with old established practice. The work was not guided by one or two editors but by a large committee. History-writing by committee seemed not only distasteful but impossible to achieve to many, both because of the practical difficulties involved and because it seemed incredible that so many editors could agree on a common text, without falling into sheer banality. Now that the volumes are out, readers can judge for themselves. Many among them actually wonder how exactly these volumes and chapters were created. Because I have been an active member of the committee since its creation in 1971 and of its bureau since 1983, I can provide a general answer to this question. But the time has also come to draw attention to the records generated by this project. Future researchers will find a huge mass of papers involving hundreds of historians of Africa that touch on practically all aspects of Africa's historiography between ca. 1965 and today.