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Psyco 350 Lec #12– Slide 1 Lecture 12 – Psyco 350, B1 Winter, 2011 N. R. Brown.

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Presentation on theme: "Psyco 350 Lec #12– Slide 1 Lecture 12 – Psyco 350, B1 Winter, 2011 N. R. Brown."— Presentation transcript:

1 Psyco 350 Lec #12– Slide 1 Lecture 12 – Psyco 350, B1 Winter, 2011 N. R. Brown

2 Psyco 350 Lec #12 – Slide 2 Outline Dual Process Models –Recognition & Remember/Know –Process Dissociation Procedure Direct Tests Indirect Tests Implicit Memory & Real-World Estimation Semantic Memory

3 Psyco 350 Lec #12– Slide 3 Remember/Know: An Example – Rajaram (1993) Exp 1. Levels of Processing R: semantic > rhyme; K: deep = shallow Exp 2. Pictures vs words R: picture > words; K: picture = word

4 Psyco 350 Lec #12– Slide 4 Remember/Know (Radvansky, pp 307-308) General Findings: factors  recollection,  “remember” LOP, repetition, short (vs long) delay Problems: poor terminology

5 Psyco 350 Lec #12– Slide 5 Remember/Know Instructions: Rajaram (1993)

6 Psyco 350 Lec #12– Slide 6 Remember/Know General Findings: factors  recollection,  “remember” LOP, repetition, short (vs long) delay Problems: poor terminology judgmental criteria r/k as confidence judgment Converging Evidence: Process dissociation studies

7 Psyco 350 Lec #12– Slide 7 Process Dissociation; Jacoby (1991) Two Independent Process: recollective (R) automatic (A) Strategy: set processes in opposition  manipulate factor(s) affecting recollection  2 tests: recollection  yes (Inclusion) recollection  no (Exclusion)

8 Psyco 350 Lec #12– Slide 8 Process Dissociation 2 tests: recollection  yes (Inclusion) recollection  no (Exclusion) Goal: Compute values for R & A Data: Inclusion = R + A(1-R) Exclusion = A(1-R) Parameter Estimates R = Inclusion – Exclusion A = Exclusion / (1-R)

9 Psyco 350 Lec #12– Slide 9 Process Dissociation Evidence for the role of Dual-Processes in two classes of memory test 1.A Direct Test (recognition) 2.An Indirect Task (fragment completion)

10 Psyco 350 Lec #12– Slide 10 Process Dissociation: Direct Test Read a list of words – List 1 Hear a list of words – List 2 Two recognition tests: –Both tests include List 1, List 2 and novel words. –Inclusion test: Respond “old” if word was on either list. –Exclusion test: Respond “old” only if word was on List 2.

11 Psyco 350 Lec #12– Slide 11 Inclusion test Inclusion test: Respond “old” if word was on either list. –Intentional (recollective) process will have a certain probability of concluding “old” for List 1 words – R –Automatic process will also have a certain probability of concluding “old” for List 1 words – A –If either process concludes “old”, the subject will respond “old” P(old) = R + A (1-R)

12 Psyco 350 Lec #12– Slide 12 Inclusion Condition List 1 Word “OLD R ” Recollected NOT Recollected High Familiarity “OLD A ” “New” Low Familiarity P(OLD) = P(OLD R ) + P(OLD A ) R% 1-R% 1-A% A%

13 Psyco 350 Lec #12– Slide 13 Exclusion test Exclusion test: Respond “old” only if word was on List 2. –Subject will only respond “old” to List 1 words if two things happen: The automatic process responds “old” due to a feeling of familiarity – A The intentional process fails to recognise the word (if it had, it would recall it was from List 1) – (1-R) P(old ) = A(1-R)

14 Psyco 350 Lec #12– Slide 14 Exclusion Condition List 1 Word “NEW” Recollected NOT Recollected High Familiarity “OLD A ” “New” Low Familiarity P(OLD) = P(OLD A ) R% 1-R% 1-A% A%

15 Psyco 350 Lec #12– Slide 15 Dissociating the processes Data: Inclusion: P(old) = R + (1- R) Exclusion: P(old) = A(1-R)

16 Psyco 350 Lec #12– Slide 16 Inclusion Condition List 1 Word “OLD R ” Recollected NOT Recollected High Familiarity “OLD A ” “New” Low Familiarity P(OLD) = P(OLD R ) + P(OLD A ) R% 1-R% A% 1-A%

17 Psyco 350 Lec #12– Slide 17 Exclusion Condition List 1 Word “NEW” Recollected NOT Recollected High Familiarity “OLD A ” “New” Low Familiarity P(OLD) = P(OLD A ) R% 1-R% 1-A% A%

18 Psyco 350 Lec #12– Slide 18 Dissociating the processes Data: Inclusion: P(old) = R + (1- R) Exclusion: P(old) = A(1-R) Parameter Estimates Inclusion – Exclusion = R A = Exclusion / (1-R)

19 Psyco 350 Lec #12– Slide 19 Jacoby (1991) Materials: List 1: READ words List 2: HEAR words Tests: Inclusion –List 1  “OLD” –List 2  “OLD” Exclusion –List 1  “NEW” –List 2  “OLD”

20 Psyco 350 Lec #12– Slide 20 Jacoby (1991; Exp 3) Two recognition tests (% “OLD” for READ words): Inclusion testP(old) = 0.48 Exclusion testP(old) = 0.37* –R = Inclusion – Exclusion = 0.11 –A = Exclusion / (1-R) = 0.37 / 0.89 = 0.42 *in exclusion condition, “OLD” are errors

21 Psyco 350 Lec #12– Slide 21 Jacoby (1991; Exps 2 & 3) Implication: When recollection is knocked out, P(OLD) in exclusion condition should equal A Exclusion test w/ digit monitoring task (monitor for 3 odd digits in a row). Expectation: Recollection eliminated by divided attention (digit task) – R = 0 Prediction: Exclusion = A(1-R) = 0.42 (1-0) = 0.42 Results: Exclusion w/ divided attention: Prob(Old) = 0.43

22 Psyco 350 Lec #12– Slide 22 Process Dissociation: Indirect Test Jacoby, Toth, & Yolelinas, (1993, Exp 1b) Study: read words full attention divided attention (  recollection) Task: stem completion: inclusion: complete with list word or guess exclusion: complete with new words only @ Test: green stem  inclusion red stem  exclusion

23 Psyco 350 Lec #12– Slide 23 Jacoby et al. (1993): Results Divided attention: Inclusion task:  P(old) Exclusion task:  P(old)

24 Psyco 350 Lec #12– Slide 24 Jacoby et al. (1993): Results Results: Inclusion:div (46%) < full (61%) Exclusion: div (46%) > full (36%) Interpretation: div attention knocked out recollection recollection  accuracy in both conditions

25 Psyco 350 Lec #12– Slide 25 Jacoby et al. (1993): Results Computing A & R Full R = I – E A = E/(1-R) 25 = 61 – 36 47=36/75 Divided R = I – E A = E/(1-R) 0 = 46 – 46 46=46/(1-0)

26 Psyco 350 Lec #12– Slide 26 Process Dissociation Procedure: Conclusion There are no process pure tasks. Both recollective/explicit & automatic/implicit processes can influence performance on both direct and indirect tests of memory

27 Psyco 350 Lec #12 – Slide 27 Implicit Memory & Judgment – Mere Exposure (Radvansky, p. 108-109) Zajonc (1969) Study: view a set of Chinese characters subliminal exposure (4 msec/charter) Test: recognition (2IFC – exposed vs new) -- OR -- preference judgment (2IFC – exposed vs new)

28 Psyco 350 Lec #12– Slide 28 Zajonc (1969): Results Recognition at chance. Preference Judgment: 65% favored exposed character.

29 Psyco 350 Lec #12– Slide 29 Zajonc (1969): Explanation (Even subliminal) exposure facilities subsequent processing fluency, i.e., speed & easy of processing –Evidence for fluency: Repetition priming effects on tasks like lexical decision & perceptual identification. People are sensitive to between-item differences in fluency, though not necessarily aware of their origins. OTBE*, people tend to attribute POSITIVE things, fluently processed stimuli. *OTBE = Other Things Being Equal

30 Psyco 350 Lec #12– Slide 30 Fluency Effects Memory & perceptual judgments: recognition recency frequency loudness Non-mnemonic Judgments: liking/preferences truth fame r-w world estimates Question: When, why, and to what extent does fluency (implicit memory) affect knowledge-based judgment?

31 Psyco 350 Lec #12– Slide 31 Estimate the current populations of the following countries. Actual Pop Estimate 1992 2006. Austria37.0 mil 7.6 mil 8.2 mil Bangladesh 15.0 mil114.7 mil 147.2 mil Nigeria16.5 mil115.6 mil 131.9 mil Norway24.5 mil 4.2 mil 4.6 mil

32 Psyco 350 Lec #12– Slide 32 “Availability Bias” & Populations Estimation 1. People tend to UNDERestimate populations of large, obscure countries.

33 Psyco 350 Lec #12 – Slide 33 “Availability Bias” & Populations Estimation 2. People tend to OVERestimate populations of small, well-known countries.

34 Psyco 350 Lec #12 – Slide 34 A Possible Explanation for Availability Bias Domain-specific knowledge & fluency-based intuitions can influence real-world estimation. For populations estimation: –People use fluency/familiarity/availability to gauge relative population size. –Assumption: better known countries have larger populations then less-well known countries.

35 Psyco 350 Lec #12 – Slide 35 Availability Terminology: Tversky & Kahneman (1973) identified the “Availability Heuristic.” when ease-of-retrieval used to estimate frequency or probability of events. Generalization: ease-of-retrieval  fluency, familiarity “availability” used in situations in which fluency is found to affect judgment and decision making.

36 Psyco 350 Lec #12– Slide 36 Availability The Logic of the Availability (fluency, familiarity) Assume: prop x correlates w/ memory Goal: prop x for item i ? Mechanism: assesses availability of info for item i. use assessment as index of prop x for item i.

37 Psyco 350 Lec #12 – Slide 37 Implicit Memory & Real-Estimation Brown & Siegler (1992) Background: availability might be a good cue for estimating population. But is it used? Reason: population & media exposure highly correlated R(New York Times index/ True Pop) =.59 Prediction: estimated population should correlate strongly w/ rated knowledge (a proxy for availability)

38 Psyco 350 Lec #12 – Slide 38 Brown & Siegler (1992): Method Materials: 100 countries Participants: 24 CMU undergrads Tasks: Rate knowledge Estimate population

39 Psyco 350 Lec #12– Slide 39 Brown & Siegler (1992): Results Important results: As predicted, R(est w/ know) quite high (.58) [R(est w/know) =.58] >> [R(est/true) =.41] Interpretation: pop-estimates based in availability-base intuitions Mean Rank-Order Correlations True Pop NYT Index Est Pop Estimated Population.41.57 Rated Knowledge.37.70.58

40 Psyco 350 Lec #12 – Slide 40 Availability & Population Estimation Interpretation: pop-estimates based in availability-base intuitions An Alterative Interpretation: People hold preexisting beliefs about the size of well- known countries. These beliefs are biased by media coverage. People infer that unknown countries are small. (Recognition Heuristic – Gigerenzer & Goldstein, 1996)

41 Psyco 350 Lec #12 – Slide 41 Availability & Population Estimation People can and do justify their estimates with reference to task relevant knowledge. Size categories are often mentioned. Comparisons w/ other countries also occur Key question: Are size categories retrieved or inferred?

42 Psyco 350 Lec #12 – Slide 42 Brown, Cui, & Gordon (2002) Aim: Determine whether population estimation is sensitive to priming, as Availability account predicts. Method: Phase 1 – rate knowledge – 52 countries (primed set) Phase 2 – estimate populations –52 primed countries & 52 unprimed countries* * primed & unprimed sets matched for estimated pop, rated kn, actual pop, actual area & region

43 Psyco 350 Lec #12 – Slide 43 Brown et al. (2002): Results Availability Prediction: Primed > Unprimed Results: Primed: 23.3 million Unprimed: 21.2 million  2.1 million* %  10% Interpretation: knowledge ratings  availability/fluency in primed set Availability/fluency influenced estimation process

44 Psyco 350 Lec #12 – Slide 44 Another Example: Fatality Estimates Task: How many Canadians died of Cause X last year? Results: reasonable correlation between estimated & true fatality rate. Availability Bias: holding true frequency constant, more vivid causes elicit  estimates

45 Psyco 350 Lec #12 – Slide 45 Another Example: Fatality Estimates Task: How many Canadians dies of Cause X last year? Results: reasonable correlation between estimated & true fatality rate. Availability Bias: holding true frequency constant, more vivid causes elicit  estimates

46 Psyco 350 Lec #12 – Slide 46 Importance of Availability Importance of availability differs across tasks. ___________________________________________________________________________________________ Determinants: actual/perceived correlation between prop x and memory quantity & credibility of competing information __________________________________________________________________________________________

47 Psyco 350 Lec #12 – Slide 47 Importance of Availability Judgment/estimation tasks that are (sometimes) display an availability bias: recency (dates, recognition), truth, fatality rates, frequency, probability, corporate sales, wealth, population Judgment/estimation tasks that do not display an availability bias: age, distance, area, latitude, longitude


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