Representation and Retrieval

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Representation and Retrieval

• Reviewing the framework
• Information processing sequence
• Encoding entering information into cognitive
  system
• Attention
• Interpretation
• Elaboration going beyond the information
• Evaluation and judgment
• Inference
• Attribution
• Representation storing new knowledge
• Retrieval using stored knowledge
• Response

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Representation and Retrieval

• So far focus on how information is processed
• Some (but not all) stimulus info encoded
  selective attention
• Interpreted
• Elaborated in various ways evaluation,
  inference, attribution

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Representation and Retrieval

• Information then stored in memory. But
• Stimulus info has been transformed. Therefore --
  
• Mental representation of it may differ from
  actual input. But
• That representation is basis for later retrieval
  and response
• So -- Use of information is based on retrieval

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Representation and Retrieval
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Representation and Retrieval

• Model does a good job of specifying
• How information is represented in memory (and
  why)
• How information is retrieved from memory

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Representation and Retrieval

• Representation, retrieval, and judgment the use
  of heuristics
• Information represented in memory -- used for
  many purposes, e.g., judgments decisions.
• Do you think Ryan is a smart guy?
• Candidate Smith is he a conservative?
• How many times have we been told the economy is
  sound?
• How are these judgments made?

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Representation and Retrieval

• Do you think Ryan is a smart guy?
• Judgment formed on-line (stored in memory) or
  memory-based (on retrieval of relevant info from
  memory)
• Candidate Smith is he a conservative?
• Image (prototype) of what a conservative is.
  How well does Mr. Smith match prototype?
  Pro-choice, but anti-gun control, pro-business,
  but anti-tax cuts, etc.
• How many times the economy is sound?
• To provide accurate answer, recall all instances
  from memory
• Problem to be accurate, judgment process can
  take a lot of work (time, energy).
• Solution short cuts heuristics. Tversky
  Kahneman (1974 Rdng. 10).

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Representation and Retrieval

• Heuristic
• a rule of thumb applied to available
  information
• allows making judgments with little processing
  effort
• yields judgments that are in most cases
  reasonably accurate.
• However --
• rule of thumb is not thorough, logical
  analysis therefore --
• can produce systematic errors and biases.

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Representation and Retrieval

• Why base judgments on error-prone process?
• All information needed to make logical judgment
  may not be available
• Person has limited capacities and resources
• Decisions need to be made quickly
• Though subject to error, heuristics usually
  produce judgments that are sufficiently accurate

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Representation and Retrieval

• Judgment heuristics
• Representativeness
• Assigning single elements (e.g., persons) to
  larger categories (e.g., groups), estimating
  probability
• Availability
• Making frequency and probability judgments

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Representation and Retrieval

• Representativeness heuristic categorization
  based on resemblance of exemplar to category
  (prototype).
• If A is highly representative of B, the
  probability that A originates from B is judged to
  be high.
• Bob is quiet and shy, reads a lot, and is
  concerned with detail and orderliness. Is Bob a
  farmer or a librarian?
• Is Candidate Smith a conservative?
• The heuristic makes sense category members
  usually do resemble prototype of category. Hence
  useful and often accurate.

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Representation and Retrieval

• Problems sources of error (see Tversky
  Kahneman reading)
• Insensitivity to base rates. Example -- exemplar
  resembles one category, but other category more
  likely. Base rates vs. representativeness.
• Conjunction fallacy.
• Linda is 31 years old, single, outspoken, and
  very bright. She majored in philosophy. As a
  student she was deeply concerned with issues of
  discrimination and social justice, and also
  participated in anti-nuclear demonstrations.
• What is probability that today
• Linda is a bank teller.
• Linda is a bank teller and a feminist.

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Representation and Retrieval

• Insensitivity to chance.
• the hot hand in basketball
• Ignoring regression to the mean.
• the Sports Illustrated jinx.
• Some names..

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• Jennifer Lopez
• Steve Whitaker
• Hillary Clinton
• Sam Mudd
• Condolesa Rice
• Jim Sherman
• John Levine
• Serena Williams
• Bruce Stuckel
• Eleanor Roosevelt
• Oprah Winfrey
• Bob Hall
• Garry Demarest
• Laura Bush
• Jeff McMillan

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Representation and Retrieval

• Availability heuristic judging frequency of
  occurrence based on ease of retrieving instances.
  
• Which occurs more frequently
• Robins or owls?
• Fords or Mercedes?
• Baseball players or soccer players?
• The heuristic makes sense. Instances in large
  classes are usually recalled more easily than
  instances in small classes.
• But -- Availability is the inverse if instances
  can be recalled easily, there must be a lot of
  them.

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Representation and Retrieval

• Of the names you saw, were there more females or
  more males?
• Females?
• Males?
• Problems sources of error ease of retrieval
  can be due to factors other than actual
  frequency. Anything that makes instances more
  accessible in memory will influence judgments.

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Representation and Retrieval

• What factors influence ease of retrieval?
• Familiarity
• Famous and not-so-famous names. Females on list
  all famous. Males not famous.
• Recency
• Salience, vividness
• Egocentric bias

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Representation and Retrieval

• Egocentric bias in retrieval of instances (Ross
  Sicoly, 1979 Rdng. 12).
• Married couples, each person indicates extent of
  their responsibility for each of 20 activities
  making breakfast, cleaning dishes, grocery
  shopping, cleaning house, planning joint
  activities, etc.
• Results add two values from partners, greater
  than total possible.
• Why? Self-relevant inputs are more available for
  retrieval from memory.

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Representation and Retrieval

• Separating amount of recall from ease of
  retrieval.
• The problem availability heuristic relies on
  ease of retrieving instances. But in many
  cases there is more recall (famous names). Is
  overestimation due to recalling more or recalling
  a few more easily?

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Representation and Retrieval

• Strategy for solving (Schwarz et al., 1991 Rdng.
  11).
• Describe 6 (12) situations in which you behaved
  assertively (unassertively).
• Rate how assertive you are.
• no. recalled assertive unassertive
• 6 6.3 5.2
• 12 5.2 6.2

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Representation and Retrieval

• Retrieval -- Different routes to retrieval
• Information in memory -- retrieved for judgments,
  decisions, etc. How will information be
  retrieved? Have already seen a few ways.
• Free recall retrieving items of acquired
  information
• Frequency estimates
• Trait ratings

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Representation and Retrieval

• Two well-known effects in the literature
• Better recall of expectancy-inconsistent items
  (e.g., Srull, 1981 Rdng. 23).
• Proportion Recalled
• Congruent .400
• Incongruent .470
• Irrelevant .278
• Overestimation of frequency of expectancy-consiste
  nt items (e.g., Hamilton Rose, 1980).
• Traits Stereotypic of
• Occupation Accts Doctors Salesmen
• Accountants 2.67 1.99
  2.25
• Doctors 2.21 2.66 2.41
• Salesmen 1.94 2.12 2.94

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Representation and Retrieval

• How can we explain both of these effects??
• The effects occur under different conditions
• Different retrieval processes for different tasks
• Return to the associative network model.

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Representation and Retrieval
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Representation and Retrieval

• The TRAP Model (Twofold Retrieval from
  Associative Pathways) (Garcia-Marques Hamilton,
  1996).
• Assumes same encoding and representation as
  network model.
• One more assumption pathways connecting person
  node to --
• consistent items -- strong (easily accessible)
• inconsistent items -- weak (less accessible)

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Representation and Retrieval

• Major proposal of TRAP Model Two strategies for
  retrieval
• Exhaustive retrieval. Example recall.
• Heuristic retrieval. Example frequency
  estimates.
• What are differences between two retrieval
  strategies?

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Representation and Retrieval

• Exhaustive Retrieval Heuristic Retrieval
• Example free recall Example frequency
  estimates
• Thorough search Selective search,
  focused on specific type of
  information
• Retrieve anything and Uses availability
  to gauge everything, in any order
  frequency or amount of
• information
• Resource-consuming Less systematic, less
  demanding
• Output retrieval of specific Output summary
  estimate
• items

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Representation and Retrieval

• Implication of TRAP Model
• Recall and frequency estimation rely on different
  retrieval strategies
• So could use both strategies to retrieve info
  from same representation
• If so in same study, could we show
• (a) better recall of incongruent items
• and
• (b) overestimation of congruent items?

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Representation and Retrieval

• Empirical test (Garcia-Marques Hamilton, 1996)
• Task form impressions of two persons.
• Method
• different occupations, opposite stereotypes
  (expectancies) cab driver (unambitious, fun),
  computer programmer (ambitious, boring)
• read 36 behaviors, 18 about each person (6
  congruent, 6 incongruent, 6 neutral per person)
• Recall behaviors
• Estimate of behaviors for each trait

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Representation and Retrieval

• Results
• Recall no. items recalled
• congruent 3.67
• incongruent 4.72
• irrelevant 3.33
• Frequency estimates
• mean estimate
• congruent 16.61
• incongruent 13.49

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Representation and Retrieval

• Conclusion two retrieval strategies exhaustive
  heuristic -- can produce
• divergent outcomes
• based on same information
• on immediately successive tasks

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Representation and Retrieval

• Next study (Garcia-Marques, Hamilton, Maddox,
  2002)
• Same basic methodology, with some manipulations
  -- intervene to alter exhaustive retrieval
• Cognitive load at encoding
• Cognitive load at retrieval
• Free recall vs. focused recall
• Dependent measure recall

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Representation and Retrieval

• Mean Recall
• No Load Load Encoding Load
  Retrieval
• Cong Inc Cong
  Inc Cong Inc
• Free Recall 4.00 5.05
• Focused Recall

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Representation and Retrieval

• Mean Recall
• No Load Load Encoding Load
  Retrieval
• Cong Inc Con Inc
  Cong Inc
• Free Recall 4.00 5.05 4.55 4.10
  4.70 4.10
• Focused Recall

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Representation and Retrieval

• Mean Recall
• No Load Load Encoding Load
  Retrieval
• Cong Inc Con
  Inc Cong Inc
• Free Recall 4.00 5.05 4.55
  4.10 4.70 4.10
• Focused Recall 4.68 4.32 4.53 3.76
  5.17 3.83

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Representation and Retrieval

• Summary of findings
• Cognitive load during either encoding or
  retrieval changes outcome (for different reasons)
• Focused recall changes outcome
• Note -- focused recall makes free recall
  (exhaustive) resemble the heuristic retrieval
  process

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Representation and Retrieval

• Remembering that vacation
• Collaborative recall retrieval as a social
  process (Garrido, 2007)
• Procedure
• 3 persons per session
• Task form impression
• Expectancy John, computer programmer,
  intelligent, wise, quick thinker
• 30 behaviors
• Recall
• Collaborative groups
• Nominal groups

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• Results --

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Representation and Retrieval

• Collaborative retrieval lower recall why?
• Relationship between encoding retrieval
• Items represented in memory
• Representation implies retrieval routes
• Normal recall -- retrieval follows those routes
• Collaborative recall
• Each person has idiosyncratic representation,
  retrieval routes
• Other person may recall item not implied by
  retrieval plan disruptive inhibits recall
• Consequence lower recall in collaborative

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Representation and Retrieval
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Representation and Retrieval

• But not the whole story
• Transactive memory (Wegner, Erber, Raymond,
  1991)
• Shared memory schemes within couple,
• Each member has special knowledge
• Both members know who knows what
• I dont need to remember stuff you know
• Together, better memory
• Should occur only in established couples

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Representation and Retrieval

• Method
• Natural impromptu couples
• Task memorize items from 7 categories
• Assignment of expertise or not (3 categories to
  one partner, 4 to other)
• Dyadic memory task

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Representation and Retrieval

• Results

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Representation and Retrieval

• Results
• No assignment natural impromptu
• Assigned expertise impromptu natural
• Why??
• No assignment pre-existing structures in
  natural couples provides advantage
• Assigned expertise
• interference of assigned structure with
  pre-existing structure
• in natural, but not impromptu, couples