this study's methods, analyses, and results differed from the previous ones. By 1971, hundreds of studies within the operant tradition (Skin-ner, 1953) had established that extrinsic rewards can control be-havior. When administered closely subsequent to a behavior, re-wards were reliably found

Evolutionary theory has always been plagued by scantiness of evidence. We see the products of evolution but not much of the process. Most of the story happened long ago, and little remains of the early stages. Especially few traces of behavior remain; only recently were there artefacts that could endure. Verbal behavior left no artifacts until the appearence of writing, and that was a very late stage. We shall probably never know precisely what happened, but we ougth to be able to say what might have happended – that is what kind of variations and what kind of contingencies of selection could have brought verbal behavior into existence. Speculation about natural selection is supported by current research on genetics; the evolution of a social enviroment or culture is supported by the experimental analysis of behavior. Strictly speaking, verbal behavior does not evolve. It is the product of a verbal enviroment or what linguistics call a language, and it is the verbal enviroment that evolves. Since a verbal enviroment is composed of listeners, it is understandable that linguistics emphasize the listener. A question often asked, for example, is

Statistical procedures for missing data have vastly improved, yet misconception and unsound practice still abound. The authors frame the missing-data problem, review methods, offer advice, and raise issues that remain unresolved. They clear up common misunderstandings regarding the missing at random (MAR) concept. They summarize the evidence against older procedures and, with few exceptions, dis-courage their use. They present, in both technical and practical language, 2 general approaches that come highly recommended: maximum likelihood (ML) and Bayes-ian multiple imputation (MI). Newer developments are discussed, including some for dealing with missing data that are not MAR. Although not yet in the main-stream, these procedures may eventually extend the ML and MI methods that currently represent the state of the art. Why do missing data create such difficulty in sci-entific research? Because most data analysis proce-dures were not designed for them. Missingness is usu-ally a nuisance, not the main focus of inquiry, but

play Man and Superman. "He who can, does. He who cannot, teaches" is a calamitous insult to our profes-sion, yet one readily repeated even by teachers. More worrisome, its philosophy often appears to under-lie the policies concerning the occu-pation and activities of teaching. Where did

Our possessions are a major contributor to and reflection of our identities. A variety of evidence is presented supporting this simple and compelling premise. Related streans of research are identified and drawn upon in devetopJng this concept and implications are derived for consumer behavior. Because the construct of exterxJed self involves consumer behavior rather than buyer behavior. It apjpears to be a much richer construct than previous formulations positing a relationship between self-concept and consumer brand choice. Hollow hands clasp ludicrous possessions because they are links in the chain of life If it breaks, they are truly losL—Dichlsr \ 964 W e cannot hope to understand consumer behav-ior without first gaining some understanding of ihe meanings that consumers attach to possessions..• \ key to understanding what possessions mean is rec-ognizing thai, knowingly or unknowingly, intention-ally or unintentionally, we regard our possessions as parts of ourselves. As Tuan argues, "Our fragile sense

Spanning seven orders of magnitude: a challenge for

The Intemet protocol suite, TCP/IP, was first proposed fifteen years ago, It was developed by the Defense Advanced Research Projects Agency (DARPA), and has been used widely in military and commercial systems. While there have been papers and specifications that describe how the protocols work, it is sometimes difficult to deduce from these why the protocol is as it is. For example, the Intemet protocol is based on a connectionless ordatagram mode of service. The motivation for this has been greatly misunderstood. This paper attempts to capture some of the early reasoning which shaped the Intemet protocols.

It is proposed that motivation may affect reasoning through reliance on a biased set of cognitive processes—that is, strategies for accessing, constructing, and evaluating beliefs. The motivation to be accurate enhances use of those beliefs and strategies that are considered most appropriate, whereas the motivation to arrive at particular conclusions enhances use of those that are considered most likely to yield the desired conclusion. There is considerable evidence that people are more likely to arrive at conclusions that they want to arrive at, but their ability to do so is constrained by their ability to construct seemingly reasonable justifications for these conclusions. These ideas can account for a wide variety of research concerned with motivated reasoning. The notion that goals or motives affect reasoning has a long and controversial history in social psychology. The propositions that motives may affect perceptions (Erdelyi, 1974), attitudes (Festinger, 1957), and attributions (Heider, 1958) have been put forth by some psychologists and challenged by others. Al-though early researchers and theorists took it for granted that motivation may cause people to make self-serving attributions

How do people know as much as they do with as little information as they get? The problem takes many forms; learning vocabulary from text is an especially dramatic and convenient case for research. A new general theory of acquired similarity and knowledge representation, latent semantic analysis (LSA), is presented and used to successfully simulate such learning and several other psycholinguistic phenomena. By inducing global knowledge indirectly from local co-occurrence data in a large body of representative text, LSA acquired knowledge about the full vocabulary of English at a comparable rate to schoolchildren. LSA uses no prior linguistic or perceptual similarity knowledge; it is based solely on a general mathematical learning method that achieves powerful inductive effects by extracting the right number of dimensions (e.g., 300) to represent objects and contexts. Relations to other theories, phenomena, and problems are sketched.

Abstract not found