Leadership and expectations: Pygmalion effects and other self-fulfilling prophecies in organizations

The Pygmalion effect is a type of self-fulfilling prophecy (SFP) in which raising manager expectations regarding subordinate performance boosts subordinate performance. Managers who are led to expect more of their subordinates lead them to greater achievement. Programmatic research findings from field experiments are reviewed, and our present knowledge about the Pygmalion effect in the management of industrial, sales, and military organizations is summarized. A model is presented in which leadership is hypothesized to be the key mediator through which manager expectations influence subordinate self-efficacy, performance expectations, motivation, effort, and performance. The behaviors that comprise the Pygmalion Leadership Style are described. Besides creating the one-on-one Pygmalion effect, additional ways for managers to assert their leadership by creating productive organizationwide SFP are suggested. An agenda for research on SFP applications is proposed.     

Diagnosing inequalities in schooling: Ogbu’s orientation and wider implications

Throughout his life, John Ogbu worked untiringly to diagnose the educational problems of minorities, with the goal of remedying them. Although his earliest works propose a comprehensive anthropological approach, his last works seem to settle into exhortations to parents and teachers to put more pressure on (involuntary) minority children whose achievements are low; and to pupils to stop grumbling and get down to taking their schoolwork seriously. In this paper, I claim that Ogbu’s work can be seen to be showing the way to the deployment of more sophisticated theoretical tools in order to attain (1) a more refined analysis of the minority status; and (2) a broader social understanding of the basis for rejecting school standards among different kinds of minorities. By resorting to the broader theoretical approach he pioneered, researchers will be able to propose more effective remedies.

‘The bourgeoisie, by the rapid improvement of all instruments of production, by the immensely facilitated means of communication …. compels all nations … to introduce what it calls civilization into their midst … In one word, it creates a world after its own image’ (Marx & Engels, Communist Manifesto, 1935 Marx K Engels F (1935/1948) The Communist manifesto in: E. Burns (Ed.) A Handbook of Marxism New York International Publishers  [Google Scholar], p. 27).     

On the trimmed mean and minimax-variance L-estimation in Kolmogorov neighbourhoods

We consider the properties of the trimmed mean, as regards minimax-variance L-estimation of a location parameter in a Kolmogorov neighbourhood K() of the normal distribution: We first review some results on the search for an L-minimax estimator in this neighbourhood, i.e. a linear combination of order statistics whose maximum variance in K_t() is a minimum in the class of L-estimators. The natural candidate – the L-estimate which is efficient for that member of K_t,() with minimum Fisher information – is known not to be a saddlepoint solution to the minimax problem. We show here that it is not a solution at all. We do this by showing that a smaller maximum variance is attained by an appropriately trimmed mean. We argue that this trimmed mean, as well as being computationally simple – much simpler than the efficient L-estimate referred to above, and simpler than the minimax M- and R-estimators – is at least “nearly” minimax.     

Inference for general parametric functions in box‐Cox‐type transformation models

The authors propose a simple but general method of inference for a parametric function of the Box‐Cox‐type transformation model. Their approach is built upon the classical normal theory but takes parameter estimation into account. It quickly leads to test statistics and confidence intervals for a linear combination of scaled or unsealed regression coefficients, as well as for the survivor function and marginal effects on the median or other quantité functions of an original response. The authors show through simulations that the finite‐sample performance of their method is often superior to the delta method, and that their approach is robust to mild departures from normality of error distributions. They illustrate their approach with a numerical example.     

ASYMMETRIC INFORMATION AND THE EXCESS VOLATILITY OF STOCK PRICES

Evidence suggests the volatility of stock prices cannot be accounted for by information about future dividends. We argue that some of the volatility of stock prices in excess of fundamentals results from fluctuations in the amount of public information over time. Our model assumes that dividends and consumption are constant in the aggregate but that there are good firms and bad firms whose identity may be unknown to the public, as in Akerlof's "lemons" problem. In that case, the collective valuation of the constant dividend stream depends on the degree of informational asymmetry.     

Distributions minimizing fisher information for scale in kolmogorov neighbourhoods

We construct those distributions minimizing Fisher information for scale in Kolmogorov neighbourhoods K_?(G) = {F|sup_x|F(x) - G(x| ? ?} of d.f.'s G satisfying certain mild conditions. The theory is sufficiently general to include those cases in which G is normal, Laplace, logistic, Student's t, etc. As well, we consider G(x) = 1 - e^-x, ? 0, and correct some errors in the literature concerning this case.