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Personnel administrators in the public sector have become more and more restrained by rules and regulations in recent years. The article looks at some of these constraints, and the effect these have an personnel practitioners to operate effectively and efficiently. The author argues that this has given rise to too much emphasis on the means rather than the ends of personnel administration in the public sector. A move towards humanism and the appreciation of people as valuable assets is advocated.

Evaluation in general and performance indicator systems in particular play an increasing role in society. We do not have a long historical set of experiences which helps us understand what exactly happens when, say, performance data for schools are made public on the internet and in news, because the emerging rules of the game in what some observers call the “knowledge society” (Stehr, 1994, 2001) and “reflexive modernization” (Beck, 1997a, 1997b) have inaugurated new relations between evaluation and performance data on the one hand and political, organizational and practical realities on the other.

The purpose of this paper is to propose a predictive model that could replace lawyers’ annual performance rankings and inform talent management (TM) in law firms.

Eight years of performance rankings of a sample of 140 lawyers from one law firm are used. Artificial neural networks (ANNs) are used to model and simulate performance rankings over time. Multivariate regression analysis is used to compare with the non-linear networks.

With a lag of one year, performance ranking changes are predicted by the networks with an accuracy of 71 percent, over performing regression analysis by 15 percent. With a lag of two years, accuracy is reduced by 4 percent.

This study contributes to the literature of TM in law firms and to predictive research. Generalizability would require replication with broader samples.

Neural networks enable extended intervals for performance rankings. Reducing the time and effort spent benefits partners and lawyers alike, who can instead devote time to in-depth feedback. Strategic planning, early identification of the most talented and avenues for tailored careers become open.

This study pioneers the use of ANNs in law firm TM. The method surpasses traditional static study of performance through its use of non-linear simulation and prediction modeling.

The rate and volume of air exchanged between the bed microclimate and the ambient environment determines in part how much heat is lost from the human body. This study investigated the ventilatory characteristics of infant over‐bedding to determine whether different combinations of bedding items (i.e. sheets, blankets, duvets) and types of tucking (i.e. loosely, firmly and swaddled/firmly tucked) affected microclimate ventilation. Microclimate volumes and air exchange rates were determined and used to calculate the ventilation indices. The presence of a duvet in the bedding combination resulted in lower ventilation indices than when bedding did not include a duvet. The type and combination of blankets did not significantly affect ventilation indices. The type of tucking had a significant effect on ventilation indices only when the assembly did not include a duvet.