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Implicit measurement II: From tasks to processes

Implicit measurement II: From tasks to processes. Keith Payne University of North Carolina at Chapel Hill.

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Implicit measurement II: From tasks to processes

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  1. Implicit measurement II: From tasks to processes Keith Payne University of North Carolina at Chapel Hill

  2. “Very absent-minded persons in going to their bedroom to dress for dinner have been known to take off one garment after another and finally to get into bed, merely because that was the habitual issue of the first few movements when performed at a later hour,” William James, 1890

  3. Environmental Dependency Syndrome Lhermitte, 1986

  4. Environmental Dependency Syndrome Lhermitte, 1986

  5. Environmental Dependency Syndrome Lhermitte, 1986

  6. Alien hand • “One hand tried to turn left when the other hand tried to turn right while driving a car,” (Doody & Jankovic, 1992)

  7. Levels of control • Whole person (e.g., Lhermitte’s EDS) • Different parts of same person ( e.g., Alien hand) • Different behavior • Different components of same behavior

  8. The cognitive monster vs. the automaticity juggernaut

  9. Overview • What is Process Dissociation and why is it useful? • Multinomial Modeling: Flexible tool for studying how intended and unintended mechanisms interact • Novel uses and new possibilities

  10. Part 1: What in the world is process dissociation, and why would I want to do that to my data?

  11. Process Dissociation • Developed by Larry Jacoby • Separates Conscious and Unconscious uses of memory • Implicit and Explicit memory tests show different results

  12. Warrington & Weiskrantz (1970): Amnesiacs Recall: _______________ Recognition: Elephant: old / new? Fragments: Ele_________

  13. Similar dissociations in healthy subjectsTulving, Schacter, & Stark (1982)

  14. Process Purity and Contamination • Dissociations suggest different forms of memory • Conscious memory for episode • Unconscious effect of experience; Don’t remember episode but the past influences the present • But, comparing implicit and explicit tests assumes the each is Process Pure • What if use conscious memory to fill in fragments? • What if unconscious memory affects guessing on explicit test?

  15. Separating processes rather than tasks • Jacoby proposed using Inclusion and Exclusion instructions for performing same task (e.g., Ele_________) • Inclusion: Complete with word from study list; If you can’t remember, then use first word that comes to mind • Exclusion: Complete with first word that comes to mind that was NOT on study list • Conscious memory would prevent using item

  16. Inclusion: Complete with word from study list; If you can’t remember, then use first word that comes to mind P (studied item) = Conscious + Unconscious * (1- Conscious ) • Exclusion: Complete with first word that comes to mind that was NOT on study list P (studied item) = Unconscious * (1 – Conscious )

  17. Inclusion: Complete with word from study list; If you can’t remember, then use first word that comes to mind P (studied item) = Conscious + Unconscious * (1- Conscious ) • Exclusion: Complete with first word that comes to mind that was NOT on study list P (studied item) = Unconscious * (1 – Conscious )

  18. Work backward to solve for Recollection & Familiarity • Conscious = P(studied item in Inclusion) – P(studied item in Exclusion) • Unconscious = P(studied item in Exclusion) / (1 – Conscious)

  19. An example (Jacoby et al., 1993)- Compared memory under Inclusion/Exclusion instructions with Full vs. Divided attention

  20. Solving the estimates • Full Attention • Conscious = .61-.36 = .25 • Unconscious = .36 / (1-.25) = .36 / .75 = .48 • Divided Attention • Conscious = .46 - .46 = 0 • Unconscious = .46 / (1-0) = .46 / 1 = .46

  21. An example: Process Estimates

  22. Assumptions • U & C independent • Engaging in 1 process does not change the other • U & C are not altered by Inclusion / Exclusion instruction

  23. Assumptions • Ways to test assumptions • Search for theory-predicted selective effects (dissociations) • Formal model fitting • When an assumption fails, does not undermine whole approach, but specific application

  24. Exercise 1 • Please do not read your answer sheet yet! • Read 10 sentences then take memory test after a delay

  25. The absent-minded professor didn't have his car keys. • Denis the Menace sat in Santa's chair and asked for an elephant. • The children's snowman vanished when the temperature reached 80. • The gymnast made a big mistake and might not win the gold medal. • King Kong stood on the Empire State Building. • The unskillful skateboarder lost his balance on the skateboard. • The Karate champion hit the cinder block. • The charming prince gently put his lips towards Snow White's cheek. • The narcotics officer pushed the door bell. • The clumsy chemist had acid on his coat.

  26. Delay Task

  27. Memory Test

  28. Grade your own… • Didn’t have (not “forgot” or “lost”) • Chair (not “lap”) • Vanished (not “melted”) • Might not win (not “lost”) • Stood on (not “climbed” or “stood on top of”) • Lost his balance on (not “fell off”) • Hit (not “broke”) • Put hit lips towards (not “kissed”) • Pushed (not “rang”) • Had acid (not “spilled acid”)

  29. Another Two Reasons…

  30. Weapon identification 200ms 100ms

  31. Explanations of weapons bias • Task dissociation • Implicit test = automatic process • Explicit test = controlled process • Process dissociation • Responses on any task reflect automatic and controlled components

  32. Process dissociation Jacoby (1991) What do subjects intend to do? To what extent do they respond as intended? What do subjects do when control fails?

  33. Process dissociation in weapon bias Control = responding as intended Automatic bias = responding based on activated stereotypes when control fails

  34. Automatic bias to respond “gun”

  35. Control over responses

  36. Process dissociation contrasts with task dissociation Even on “implicit measure,” the interaction of Automatic and Controlled processes key Same degree of Automatic activationproduced more or less behavioral bias, depending on Control

  37. Interim Conclusions • Blends of multiple processes are common, even within single behavior • Process Dissociation allows taking apart complex behavior into simpler processes • Sub-processes often related differently to variables of interest

  38. Part 2: Broadening the Scope: Process Dissociation as a special case of a more general family of models

  39. The cognitive monster vs. the automaticity juggernaut

  40. A Graphic Illustration of PD Control Automatic 1 - Control 1 - Automatic Note: + = Automatic-consistent response; -- = Non-automatic response

  41. An alternative model Automatic Control 1 - Automatic 1 - Control

  42. Multinomial Modeling(Batchelder & Reifer, 1990) • Data comes from experiment • Use computer algorithm to solve For parameters (estimates) • Fit test: Compares predicted responses from model against actual data. Large discrepancies = poor fit. • Can compare competing models

  43. Control-dominating Model Control Succeeds C Automatic Influence Stereotypical A 1-C Control Fails Automatic InfluenceCounter-Stereotypical 1-A Automaticity-dominating Model Automatic Influence A Control Succeeds C No Automatic Influence 1-A Control Fails 1-C

  44. Quad Model for implicit attitude/stereotype tasks(Conrey, Sherman, Gawronski, Hugenberg, & Groom, 2005)

  45. “One of psychology’s fundamental insights is that judgments are generally the products of nonconscious systems that operate quickly, on the basis of scant evidence, and in a routine manner, and then pass their hurried approximations to consciousness, which slowly and deliberately adjusts them.” Daniel Gilbert, 2002

  46. More consistent with dual process theories? Control Succeeds C Automatic Influence Stereotypical Control Fails 1-C A 1-A Automatic InfluenceCounter-Stereotypical Control Succeeds C Control Fails 1-C

  47. =

  48. Three points so far These models have no temporal order Control-dominating model is consistent with theories emphasizing fast automatic process and slow controlled process

  49. Quad-Model (Algebraically Equivalent Version) C-dominant Model with Guessing Control Succeeds C Control Dominates Automatic Influence A 1-C Control Fails Guess X OB G No Automatic Influence 1-A Guess Y 1-G A-dominant Model with Guessing 1-OB Automatic Influence A Automaticity Dominates Control Succeeds C 1-A No Automatic Influence Guess X G 1-C Control Fails Guess Y 1-G Examples from Weapon-Bias Task

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