8) Concepts & Categories
Concepts = Categories
Natural Categories
Characteristics
Basic level categories
Family resemblance
Internal structure (typicality + family resemblance)
Fuzzy sets (ill-defined boundary)
Properties
Are they always preferred?
Semantic memory lecture (Patterson)
Concepts = internal representations
Categories = "out here in the world"
Useful
Hubs: efficent way to integrate our knowledge
Easier to detect semantic similarities across concepts that are different in modality specific attributes (prawns & scallops look different but are similar conceptually)
Category: A class of stimuli that are treated in an equivalent manner
Cut down diversity of objects & events that must be dealt with uniquely (eg. allergy to scallop generalised to allergy to seafood)
Generalise helps survival of an organism with limited capacity
Natural categories
Occur in natural language (eg. fruit, animal, tool, furniture, clothing)
Rosch's work= suggests a correlational structure
Unlike artificial categories: features are not combined arbitrarily
Artificial category learning study (Bruner 1956)
Shape (3), Colour (3), No of shapes (3), No of borders (3)
S Task: work out concept experimenter has in mind
(Eg. Black (colour) cards with circles (shape)
Concept universe: 4 feature dimensions (3 x 3 x 3 x 3 = 81 possible cards)
Features may be combined arbitrarily
Feature dimensions are not independent, they are correlated
If category member "Has feathers' it is also likely to "has a beak" but not "has petals"
Artificial categories: feature dimensions are independent & can be combined arbitrarily "black" with "circle" or "square" or "cross" equally
Typicality
(McCloskey & Glucksberg): Asked Ss to decide category membership for each exemplar-category pair twice a month apart
Some exemplars (eg. bookend-furniture) low between-subject agreement and within subject consistency
Artificial categories: boundaries are clearly defined
( Wittgenstein, 1953) "Game" no attributes that are shared by ALL members of the category
No single attribute shared by ALL members of a category
But each member has at LEAST 1 attribute in common with other members
Boards? (No, ball games)
Winners and losers (No, solitaire?)
Amusement? (No, serious games?)
(Rosch & Mervis, 1975) Eg. Different types of fruit rated for typicality on a (1-7) scale: typicality is not uniform
Orange (1.07), coconut (4.50), tomato (5.57)
Typicality + Family resemblance = high correlation
(Rosch & Mervis, 1978) Ss listed attributes possessed by each exemplar of a category (eg. bird)
Derived the family resemblence score: sum of the weighted scores of attributes
Greater weight given to attributes shared with other exemplars
Robin = 13, Swallow = 13, Penguin = 3
High correlation between rated typicality and family resemblance score
Eg. Robin (high) VS penguin (low scores): typical exemplars share more attributes in common with other members of the category
Prototype: member of a category having the highest family resemblance scores (eg. apple prototype of fruits)
Internal structure
Family resemblance: better exemplars share more attributes in common with other exemplars
A category is centred around a prototype
Typicality gradient: some members of a category are better exemplar (more typical) than others (eg. apple more typical than coconut)
Subordinate (furniture) --> Basic-level (chair, desk) ---> Subordinate (arm chair, office chair)
Basic level category: best balance between informativeness & distinctiveness
Many attributes are common to members within the category (subordinates)
Few attributes in common with members of other categories
Most general level: people use similar motor movements when interacting with category members (eg. chairs but not tables sitting)
Informative
Communication = effective (Chair broke, not a piece of furniture broke)
Learned first by children: car not vehicle
Expressed economically: short name (chair > arm chair)- simple sign language gestures
Experts prefer subordinate names
Faces: matched faster to subordinate level than basic level (Benedict Cumberbatch > a human face)
Dog experts: Beagle, Terrier, Labrador
Is expertise necessary for "subordinate shift" (Anaki & Bentin, 2009)
Down-shift from basic to subordinate level: familiar objects as well as faces/objects of expertise
Eg. towers, bridges that are familiar
Superordinate: Living/non-living, Basic: monkey/human (face), tower/bridge, Subordinate (exemplar) familiar faces & towers (eg. Benedict Cumberbatch, Tower of Pisa)
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