Lecture 14 – Psyco 350, B1 Fall, 2011
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Transcript of Lecture 14 – Psyco 350, B1 Fall, 2011
Lecture 14 – Psyco 350, B1Fall, 2011
N. R. Brown
Psyco 350 Lec #14– Slide 2
Outline
1. Semantic Memory• Network Models
• The Nelly Study
• Scripts/Schemata
2. Discrepant Partner Reports and the MSP– The Discrepancy
– MSP
Psyco 350 Lec #14– Slide 3
Neely (1977)
Basic Premises: 2 components to priming
Automatic component:
fast, effortless, unaffected by intention/expectation
Controlled component:
Attentional, Slow, Effortful, Benefits (if correct) Costs (if incorrect)
Psyco 350 Lec #14– Slide 4
Neely (1977)
Goal: Contrast automatic & controlled priming
Task:
Lexical Decision -- Timed Word/Non-word Decision
Trial:
Prime Target Response
SOA RT
SOA = Stimulus Onset Asynchrony
Psyco 350 Lec #14– Slide 5
Neely (1977): Design
Prime-Target*
ExpectationX Relation X SOA .
No Shift 250 msec
Shift 400 msec
700 msec
2000 msec
* see next slide
Psyco 350 Lec #14– Slide 6
No Shift Trials: See Bird as prime expect a bird name as target.
1. Neutral XXXX-- robin2. No Shift BIRD -- robin3. Shift (unexpected) BIRD -- arm
Shift Trials: See Building as prime, expect a Body Part as target.
1.Neutral XXXXX -- window2. No Shift BUILDING -- window3. Shift (expected) BUILDING -- leg4. Shift (unexpected) BUILDING -- robin
Psyco 350 Lec #14– Slide 7
No Shift Trials: See Bird as prime expect a bird name as target.
1. Neutral XXXX-- robin2. No Shift BIRD -- robin 80% primed trials3. Shift (unexpected) BIRD -- arm 20% primed trials
Shift Trials: See Building as prime, expect a Body Part as target.
1.Neutral XXXXX -- window2. No Shift BODY -- leg 10% primed trials3. Shift (expected) BODY – window 80% primed trials4. Shift (unexpected) BODY – robin 10% primed trials
Psyco 350 Lec #14– Slide 8
Neely (1977): Results
A Priming Effect: Neutral Trials - Primed Trials
Two Type of Priming Effects:
1. Facilitation Effects -- Positive Priming
• Priming effect is positive -- Neutral > Primed
2. Inhibition Effect -- Negative Priming
• Priming effect is negative -- Neutral < Primed
Psyco 350 Lec #14– Slide 9
Neely (1977) Results – NO Shift Expected
1. No-shift, same-category pairs (Bird-robin):
• Substantial facilitation at all SOA.
2. Shift, different-category pairs (Bird-arm):
• Inhibition increases with SOA
Psyco 350 Lec #14– Slide 10
Neely (1977): Results – Shift Expected
1. Expected Shift (BODY –door):
• Facilitation increases with SOA
2. No-shift, same-category (BODY -- heart):
• Facilitation at smallest SOA• Increasing inhibition at longer
SOAs
Psyco 350 Lec #14– Slide 11
Neely (1977): Results – Shift Expected
1. Expected Shift (Building-leg):
• Facilitation increases with SOA
2. No-shift, same-category pairs (Building-window):
• Facilitation at smallest SOA• Increasing inhibition at longer
SOAs
3. Shift to unexpected category (BODY - robin)
• Inhibition at all SOAs • Inhibition increases with SOA
Psyco 350 Lec #14– Slide 12
Neely (1977): An Explanation
1. Automatic Spreading Activation: • Originates at prime, spreads to related concepts, decays
rapidly.
2. Attention required to maintain activation over longer SOAs.
Psyco 350 Lec #14– Slide 13
Neely (1977): An Explanation
3. Focusing attention on one category:
• facilitates (primes) processing of category members
• interferes with the processing (reading/word recognition) of items from other categories
Psyco 350 Lec #14– Slide 14
Neely (1977): An Explanation
4. In the Shift-Expected condition, subjects shift attention to & maintain attention for cued category
• It takes time to shift attention to new category.
• Once attention is shifted, focus is on the new category.
Psyco 350 Lec #14– Slide 15
Neely (1977): An Explanation
Shifting categories takes times.
Maintaining focus on indicated category:• facilities processing of focal category members• reduces attentional resources required to read & decide
whether letter string is a word.
Psyco 350 Lec #14– Slide 16
Semantic Networks & Priming
• Semantic Network– general knowledge representation– based on relatedness, meaning-based similarity
• Spreading Activation– automatic consequence of processing a related
information
– preparation for encountering the expected
• Activated concepts sometimes equated w/ consciousness & focal elements of WM (Cowan)
Psyco 350 Lec #14– Slide 17
Schemata & Scripts
Schemata:• Complex, stable knowledge structures
– occupations, geographical/architectural layouts, story structures, etc.
Scripts:Schemata representing stereotypical event sequences
Assumption – this knowledge is represented in semantic memory & used extensive in planning, comprehension, and recall (reconstruction)
Psyco 350 Lec #14– Slide 18
Schemata
Bartlett 1st to recognize importance of schemata.
“War of the Ghosts” Study• English undgrads read a North American Indian
legend twice.• Recalled the story once after 15 min and then over of
the course of several month
Psyco 350 Lec #14– Slide 19
Bartlett – War of the Ghosts
Main Findings:• Reproduction distorted in ways that brought the story
increasing in lines with European:
– narrative conventions
– beliefs re: physical & biological causality
Interpretation:
• Participants combined fragmentary story memory with schematic knowledge to reconstruct a “sensible” story.
Psyco 350 Lec #14– Slide 20
Schemata: General Findings
When present:• Schema-consistent info, well remembered
• Schema-inconsistent info, less well remembered.
When NOT present:
• Schema-consistent info often falsely remembered (schema-driven reconstruction)
• Schema-inconstant info generally not falsely remembered
Psyco 350 Lec #14– Slide 21
Recognizing Script-based Materials: Hannigan & Reinitz (2001)
• Schemata that capture general information about routine event sequences
– Eating in a restaurant, attending a movie, a visiting a doctor’s office, attending class, going to the beach
• Scripts identify central (& less central) actions & typical (& atypical) roles, & props.
• When not specified (or experienced) central actions & typical roles & props inferred/reconstructed
Psyco 350 Lec #14– Slide 22
Hannigan & Reinitz (2001): Method
Materials: • four 13-slide sequences
– a sequence represented one script-based activity (e.g. grocery shopping)
– including• HIGH schema-relevant items (e.g. get shopping
cart) • LOW schema-relevant items (e.g., put food on
belt)
– Presentation: 5.5 s/slide
Psyco 350 Lec #14– Slide 23
Hannigan & Reinitz (2001): Method
Psyco 350 Lec #14– Slide 24
Hannigan & Reinitz (2001): Method
Test Phase:0-to-5 Recognition Confidence Judgment on each slide:• 0 = certain slide not seen• 5 = certain slide was seen
Design:
Item Type X Schema-relevance X Delay
OLD high 15 min
NEW low 48 hr
Psyco 350 Lec #14– Slide 25
Hannigan & Reinitz (2001): Results
For OLD items:• Reco very good• high > low
For NEW items @ 15 min delay:
• high > low• tendency to
infer/reconstruct stronger for high-relevance items
Delay
15-Min 48-HR
Rec
ogni
tion
Con
fiden
ce
0
1
2
3
4
5HO
HO
LO LO
HN
HN
LN
LN
High-OLD HOLow-OLD LOHigh-NEW HNLow-NEW LN
Psyco 350 Lec #14– Slide 26
Hannigan & Reinitz (2001): Results
Effect of Delay:• OLD items: memory still
very good• False recognition
greatly for high-relevance items
Delay
15-Min 48-HR
Rec
ogni
tion
Con
fiden
ce
0
1
2
3
4
5HO
HO
LO LO
HN
HN
LN
LN
High-OLD HOLow-OLD LOHigh-NEW HNLow-NEW LN
Psyco 350 Lec #14– Slide 27
Semantic Memory: Main Points
Semantic networks can represent simple facts and reflect conceptual similarity/relatedness
Semantic priming is well established process• serves to prime related informationSchemata/scripts – complex, stable knowledge
structures • captures generalizations re: complex, but regular
features of experience.• facilitate/bias perception & memoryChallenge:
Develop detailed extensions of these notions to deal with full range of knowledge domains & modalities
Psyco 350 Lec #14– Slide 28
Memory for “How Many”
Modal explicit memory test:
• Memory for “what”
Other explicit memory test focus on event properties:
• when – event age/date/recency, list position
• where – physical location
• physical properties – appearance/sound/smell
• how often/how many – frequency
Psyco 350 Lec #14– Slide 29
Memory for “How Many”
Theoretical Issues:
• Understand the impact of repetition on memory.
• Why is frequency performance often very good?
• How is frequency information represented, updated, & used?
• How and when is frequency information used to inform probability judgments and prediction?
Psyco 350 Lec #14– Slide 30
Memory for “How Many”
Practical Issue:
• Self-reported “behavioral frequency” questions common in surveys & scales.
– business, government, Social Sciences, medicine (epidemiology)
• When are estimates accurate/inaccurate?
• When/why are they inaccurate/biased?
• Is there anyway to improve accuracy?
Psyco 350 Lec #14– Slide 31
A Commonly Asked Frequency Question
Psyco 350 Lec #14– Slide 32
Importance
• Epidemiology
• Sociology
• Psychology
• Methodology
♂SPs = ♀SPs
SP = sex partner
Psyco 350 Lec #14– Slide 33
♂SP Mean = ♀SP Means
F M
F M
F M
F M
F M
Psyco 350 Lec #14– Slide 34
♂SP Mean = ♀SP Means
F M
F M
F M
F M
F M
(♀SP = 2) = (♂SPs = 2)
Psyco 350 Lec #14– Slide 35
♂SP Mean = ♀SP Means
F M
F M
F M
F M
F M
Psyco 350 Lec #14– Slide 36
♂SP Mean = ♀SP Means
F M
F M
F M
F M
F M
(♀SP = 2) = (♂SPs = 2)
Psyco 350 Lec #14– Slide 37
The Discrepancy
♂s report far more opposite-sex SPs than ♀s
Magnitude:
• 2 X – 4X
Generality:
• US, UK, France, Canada, Norway, New Zealand
Psyco 350 Lec #14– Slide 38
SP Discrepancy as Case Study:
Explanations
Sampling Response
Social Cognitive
Psyco 350 Lec #14– Slide 39
Sampling Account (Brewer, et al 2000)
• Prostitutes under-sampled
• Support: – adjustment =
estimate[# CSW]* estimate [# partners/CSW]
– adjustment reduces discrepancy
• Problems
– implication: For ♂s, ≈75% SP are CSWs
– Wiederman (1997) – removing “Johns” reduces discrepancy slightly, but does not eliminate it.
Psyco 350 Lec #14– Slide 40
Social Account: Self-Presentation
Bad-faith Explanations
• Respondents are "telling themselves and others enormous lies“ -- Lewontin
• "Intentional misreports are the main source of the discrepancies.” -- Smith
Psyco 350 Lec #14– Slide 41
Social Account: Self-Presentation
Bad-faith Explanations
Assumed to Reflect a socially prescribed Directional Biases
The-Macho-and-the-Maiden Hypothesis:
• ♂ exaggerate
• ♀ minimize
Psyco 350 Lec #14– Slide 42
The Social Account: Support
Intuition
Robust attitude differences (Oliver & Hyde, 1993)
Psyco 350 Lec #14– Slide 43
The Stakes
Bad-Faith Partner Estimates
Undermine credibility of self-report
placing "all scientific sociology...in deep trouble” -- Lewontin
Psyco 350 Lec #14– Slide 44
A Problem for the Social Account
Problem:• Non-discrepant response patterns are the norm --
duration, frequency, activities, # past-year SPs• Example: Laumann et al. (1994)
Psyco 350 Lec #14– Slide 45
A Cognitive AccountThe Multiple Strategies Perspective
Links the discrepancy to between-sex differences in strategy use.
Identifies common strategies w/ explicable bias
• Enumeration underestimation
• “Rough Approximation” overestimation
Psyco 350 Lec #14– Slide 46
Multiple Strategy Perspective
• multiple strategies
• multiple representations
• encoding content
• content strategy
• strategy performance
References:• Blair & Burton, 1987; Brown, 1995, 1997, 2002, in press; Burton &
Blair, 1991; Conrad et al, 1998, 2003; Menon, 1993.
Psyco 350 Lec #14– Slide 47
encoding factors
contents
effort bias accuracy
strategy
Psyco 350 Lec #14– Slide 48
Multiple Strategy Perspective
• Encoding factors determine task-relevant contents of memory.
• Contents of memory restrict strategy selection.
• Strategy selection and response bias often related.
Psyco 350 Lec #14– Slide 49
An Empirically Derived Taxonomy of Frequency Estimation Strategies
Psyco 350 Lec #14– Slide 50
Relating Encoding, content, strategy & Performance
encoding content Strategy performance
‘memorable’events
‘on-target’ instances
on-target enumeration RT frequnderestimation
regularity rate rate retrieval fast, flat RTheaping
intent tally tally retrieval fast, flat RTaccurate(?)
frequent presentation
vague quantifier
impression retrieval fast, flat RToverestimation
indistinct instances
fluencymemory assessment fast, flat RT
overestimation
encoding/test mismatch
‘off-target’ instances
off-target enumerationSLOW, flat RTregressive estimates