Miller (1956) summarized evidence that people can remember about seven chunks in short-term memory (STM) tasks. However, that number was meant more as a rough estimate and a rhetorical device than as a real capacity limit. Others have since suggested that there is a more precise capacity limit, but that it is only three to five chunks. The present target article brings together a wide variety of data on capacity limits suggesting that the smaller capacity limit is real. Capacity limits (...) will be useful in analyses of information processing only if the boundary conditions for observing them can be carefully described. Four basic conditions in which chunks can be identified and capacity limits can accordingly be observed are: (1) when information overload limits chunks to individual stimulus items, (2) when other steps are taken specifically to block the recoding of stimulus items into larger chunks, (3) in performance discontinuities caused by the capacity limit, and (4) in various indirect effects of the capacity limit. Under these conditions, rehearsal and long-term memory cannot be used to combine stimulus items into chunks of an unknown size; nor can storage mechanisms that are not capacity-limited, such as sensory memory, allow the capacity-limited storage mechanism to be refilled during recall. A single, central capacity limit averaging about four chunks is implicated along with other, noncapacity-limited sources. The pure STM capacity limit expressed in chunks is distinguished from compound STM limits obtained when the number of separately held chunks is unclear. Reasons why pure capacity estimates fall within a narrow range are discussed and a capacity limit for the focus of attention is proposed. Key Words: attention; enumeration; information chunks; memory capacity; processing capacity; processing channels; serial recall; short-term memory; storage capacity; verbal recall; working memory capacity. (shrink)

Mark Wilson presents a highly original and broad-ranging investigation of the way we get to grips with the world conceptually, and the way that philosophical problems commonly arise from this. He combines traditional philosophical concerns about human conceptual thinking with illuminating data derived from a large variety of fields including physics and applied mathematics, cognitive psychology, and linguistics. Wandering Significance offers abundant new insights and perspectives for philosophers of language, mind, and science, and will also reward the interest of psychologists, (...) linguists, and anyone curious about the mysterious ways in which useful language obtains its practical applicability. (shrink)

In the beginning, there was the DN (Deductive Nomological) model of explanation, articulated by Hempel and Oppenheim (1948). According to DN, scientific explanation is subsumption under natural law. Individual events are explained by deducing them from laws together with initial conditions (or boundary conditions), and laws are explained by deriving them from other more fundamental laws, as, for example, the simple pendulum law is derived from Newton's laws of motion.

The last two decades have seen a rising interest in (a) the notion of a scientific phenomenon as distinct from theories and data, and (b) the intricacies of experimentally producing and stabilizing phenomena. This paper develops an analysis of the stabilization of phenomena that integrates two aspects that have largely been treated separately in the literature: one concerns the skills required for empirical work; the other concerns the strategies by which claims about phenomena are validated. I argue that in order (...) to make sense of the process of stabilization, we need to distinguish between two types of phenomena: phenomena as patterns in the data ( surface regularities ) and phenomena as underlying (or hidden ) regularities. I show that the epistemic relationships that data bear to each of these types of phenomena are different: Data patterns are instantiated by individual data, whereas underlying regularities are indicated by individual data, insofar as they instantiate a data pattern. Drawing on an example from memory research, I argue that neither of these two kinds of phenomenon can be stabilized in isolation. I conclude that what is stabilized when phenomena are stabilized is the fit between surface regularities and hidden regularities. (shrink)

This paper provides an interpretation of Hans-Jörg Rheinberger’s notions of epistemic things and historical epistemology . I argue that Rheinberger’s approach articulates a unique contribution to current debates about integrated HPS, and I propose some modifications and extensions of this contribution. Drawing on examples from memory research, I show that Rheinberger is right to highlight a particular feature of many objects of empirical research (“epistemic things”)—especially in the contexts of exploratory experimentation—namely our lack of knowledge about them. I argue that (...) this analysis needs to be supplemented with an account of what scientists do know, and in particular, how they are able to attribute rudimentary empirical contours to objects of research. These contours are closely connected to paradigmatic research designs, which in turn are tied to basic methodological rules for the exploration of the purported phenomena. I suggest that we engage with such rules in order to develop our own normative (epistemological) categories, and I tie this proposal to the idea of a methodological naturalism in philosophy of science. (shrink)

The data presented in the target article make a persuasive case for the notion that there is a fundamental limit on short term memory (STM) of about four items. Two possible means of further testing this claim are suggested and data regarding scene coherence and memory capacity for ordered information are reviewed.

Cowan's review shows that a short-term memory limit of four items is consistent with a wide range of phenomena in the field. However, he does not explain that limit, whereas an existing theory does offer an explanation for capacity limitations. Furthermore, processing capacity limits cannot be reduced to storage limits as Cowan claims.

Cowan postulates that the capacity of short-term memory is limited to the number of items to which attention can be simultaneously directed. Unfortunately, he endows attention with unexplained properties, such as being able to locate the most recent inputs to short-term memory, so his theory does little more than restate the data.

Cowan fails to obtain a magical number of 7 because his analysis is faulty. This is revealed by an alternative analysis of Cowan's own tasks. The analysis assumes a number 7 for adults, and neoPiagetian mental- capacity values for children. Data patterns and proportions of success (reported in Cowan's Figs. 2 and 3) are thus quantitatively explained in detail for the first time.

Cowan assumes a unitary capacity-limited attentional focus. We argue that two main problems need to be solved before this assumption can complement theoretical knowledge about human cognition. First, it needs to be clarified what exactly the nature of the elements (chunks) within the attentional focus is. Second, an elaborated process model needs to be developed and testable assumptions about the proposed capacity limitation need to be formulated.