Cognition, 34 (1990) 201-202
isc
ostulates ca GEORGEDUNBAR’ Centre for Cognitive Science, Unirpersity of Edinburgh Dunbar, G. (1990). What meaning postulates can do. Cognition,
34: 201-202.
Johnson-Laird (1987) gives an interesting review of studies of wcrd meaning and makes some intriguing proposals. In this brief note, however, I take issue with his claim that data from Johnson-Laird, Gibbs, and de Mowbray (1978) cannot be modelled using meaning postulates. His demonstration that this is ss) depends on certain assumptions about the form of the meaning postulate subjects would search for. He claims that “they should search for postulates of the following form: For any X, if x is a {plate, jug, hammer, vase],tl~en x is consumable, ‘..
and fail to find them” (p. f93). But to prescribe which postulates exist and the order in which they are searche is to place an unnecessary constraint on the device he criticises. A meaning post,ulate account can work, if it is not burdened with the additional assumptions prescribed, but is instead granted some others. Specifical;,-, let us assume that the subject engages, in parallel, in seriai searches of two stacks of mearing postulates: Stack vx Vx Vx
1 (XE {jug, knif; ,&. >) + x is not a substance (XE {sherry, ;;mmonia. , . .)‘i -+ x is a substance (xe {toffee, wood, . ..}) + x is a solid
Stack vx vx Vx vx
2 (xe {vase, syringe, . ..>) + x is not connected with consumption (XE (jug, toffee, . ..I) + x is connected with consumption (XE (toffee, plate, . ..I) --P x is connected with eating (xe {toffee, cake, . ..}) -+ x is consumable
Searching of each stack terminates when the key pos”rulate is arrived at, or when the word being evaluated is eliminated either by a negative consequent or by an antecedent within whose domain it does not fall. ‘The fundamental
*
Please address correspondence to George Dunbal , i3entre for Cogr#irive Science, University of Edinburgh, 80 South Bridge, Edinburgh EHl lHN, UK.
OOlO-0277/90/$1 .I’00 1990, Elsevier Science P~&lishersBY.
202
George Dunbar
assumption that makes this model work is that search proceeds from less specific to more specific meaning postulates. One further assumption: for each rule an item passes (apart from negative rules), add 0. I to the probability of recall. For example, R$$X passes tws rules in Stack 1, and three in Stack 2; while plate passes no rules in Stack 1, but two in Stack 2. The predicted probabilities of recall are tabulated along with the percentage of words correctly recalled, as reported by Johnson-Laird, Gibbs, and Mowbray 1978, in Table 1. Table 1.
Compariqon of predicted and obtained recall Word
Predicted probability
Obtained percentage recall
vase jug plate petrol beer coal toffee
0 0.1 0.2 0.1 0.2 0.2 0.5
8.1 10.6 16.2 10.6 21.5 21.5 50
--
This model gives a fairly good fit to the recall data, accounting for a little over 95% of the varianct of the means reported (r = 6.9766). The object is not, however, to propose a serious model of behaviour, but simply to demonstrate the general point that meaning postulates could handle such data. eferences Johnson-Laird, P.N. (1987). The mental representation of the meaning of words. Cognition,25, 189-211. Johnson-Laird. P.N., Gibbs, G., dc de Mowbray, J. (1978). Meaning, amount of processing, and memory for words. Wwnry mid Cognition, 6,372-375.
isc
ostulates ca GEORGEDUNBAR’ Centre for Cognitive Science, Unirpersity of Edinburgh Dunbar, G. (1990). What meaning postulates can do. Cognition,
34: 201-202.
Johnson-Laird (1987) gives an interesting review of studies of wcrd meaning and makes some intriguing proposals. In this brief note, however, I take issue with his claim that data from Johnson-Laird, Gibbs, and de Mowbray (1978) cannot be modelled using meaning postulates. His demonstration that this is ss) depends on certain assumptions about the form of the meaning postulate subjects would search for. He claims that “they should search for postulates of the following form: For any X, if x is a {plate, jug, hammer, vase],tl~en x is consumable, ‘..
and fail to find them” (p. f93). But to prescribe which postulates exist and the order in which they are searche is to place an unnecessary constraint on the device he criticises. A meaning post,ulate account can work, if it is not burdened with the additional assumptions prescribed, but is instead granted some others. Specifical;,-, let us assume that the subject engages, in parallel, in seriai searches of two stacks of mearing postulates: Stack vx Vx Vx
1 (XE {jug, knif; ,&. >) + x is not a substance (XE {sherry, ;;mmonia. , . .)‘i -+ x is a substance (xe {toffee, wood, . ..}) + x is a solid
Stack vx vx Vx vx
2 (xe {vase, syringe, . ..>) + x is not connected with consumption (XE (jug, toffee, . ..I) + x is connected with consumption (XE (toffee, plate, . ..I) --P x is connected with eating (xe {toffee, cake, . ..}) -+ x is consumable
Searching of each stack terminates when the key pos”rulate is arrived at, or when the word being evaluated is eliminated either by a negative consequent or by an antecedent within whose domain it does not fall. ‘The fundamental
*
Please address correspondence to George Dunbal , i3entre for Cogr#irive Science, University of Edinburgh, 80 South Bridge, Edinburgh EHl lHN, UK.
OOlO-0277/90/$1 .I’00 1990, Elsevier Science P~&lishersBY.
202
George Dunbar
assumption that makes this model work is that search proceeds from less specific to more specific meaning postulates. One further assumption: for each rule an item passes (apart from negative rules), add 0. I to the probability of recall. For example, R$$X passes tws rules in Stack 1, and three in Stack 2; while plate passes no rules in Stack 1, but two in Stack 2. The predicted probabilities of recall are tabulated along with the percentage of words correctly recalled, as reported by Johnson-Laird, Gibbs, and Mowbray 1978, in Table 1. Table 1.
Compariqon of predicted and obtained recall Word
Predicted probability
Obtained percentage recall
vase jug plate petrol beer coal toffee
0 0.1 0.2 0.1 0.2 0.2 0.5
8.1 10.6 16.2 10.6 21.5 21.5 50
--
This model gives a fairly good fit to the recall data, accounting for a little over 95% of the varianct of the means reported (r = 6.9766). The object is not, however, to propose a serious model of behaviour, but simply to demonstrate the general point that meaning postulates could handle such data. eferences Johnson-Laird, P.N. (1987). The mental representation of the meaning of words. Cognition,25, 189-211. Johnson-Laird. P.N., Gibbs, G., dc de Mowbray, J. (1978). Meaning, amount of processing, and memory for words. Wwnry mid Cognition, 6,372-375.
