1. 3 rd International Lab Meeting – Summer session 2005 11 th Edition of the International Summer School of the European Ph.D. on Social Representations and Communication Social Representations in action and construction in Media and Society “Applying the Facet Theory and Statistical Analysis via HUDAP software to Research on Social Representations: Theoretical and Methodological Computer Mediated Training Sessions” at the European PhD on Social Representations & Communication Multimedia LAB & Research Center in Rome Advantages and limitations of Facet Theory compared to other approaches Prof. Dov Elizur Dr. Eyal Yaniv

2. Advantages and limitations of Facet Theory compared to other approaches Prof. Dov Elizur Dr. Eyal Yaniv

3. Facet Theory versus other approaches Strategy for constructing meaningful scientific theory Guidelines for: Systematic design of research Formulation of hypotheses, regional hypotheses Designing observations to cover the content universe - Content sampling Parsimony – number.of dimensions Tools for data analysis and test structural hypotheses Fruitfulness –intension and extension of research Comparability of research - Cumulative science

4. Limitations No clear guidelines how to discover the basic facets of a content universe. Requires abstract thinking

5. Scientific Theory We find various definitions for theory: –We can recognize two elements: Concepts – defined by people Empirical observations – external to people

6. Guttman’s definition for theory A theory is an hypothesis of a correspondence between a definitional system for a universe of observations and an aspect of the empirical structure of those observations, together with a rationale for such an hypothesis. Let us consider its components

7. Sets and set products Set - a well defined collection of objects A: weight - a1 light a2 heavy B: height - b1 short b2 tall Set product: A set whose elements are a combination of other sets. i.e a1b1 light and short a1b2 light and tall b2a1 heavy and short b2a2 heavy and tall

8. Cartesian space B: height light heavy tall short A:weight a1b1 a1b2 a2b2a2b1

9. Main components in social research 1.Population P 2.Stimuli (questions) on content universe C 3.Group of possible responses - range R Mapping of cartesian group: Population} {Content}  (Range)}

10. Mapping Sentence The mapping sentence describes the definitional framework for observations, includes the: –subjects –content facets –range and combines them together in a regular sentence

11. Examples: Work values Personal values Intelligence Achievement Motive Organizational culture and IT

12. VALUES NORMATIVE STANDARDS TO JUDGE AND TO CHOOSE AMONG ALTERNATIVE MODES OF BEHAVIOR (KLUCKHOHN, 1952) DESIRABLE OR IMPORTANT STATES, OBJECTS, GOALS, OR BEHAVIORS, TRANSCENDING SPECIFIC SITUATIONS AND APPLIED AS NORMATIVE STANDARDS … (Schwartz & Bilsky, 1987)

13. VALUES ITEMS ESTIMATING THE IMPORTANCE OF A GOAL IN LIFE AREA (y) and RANGE ordered from very IMPORTANT to VERY UNIMPORTANT Guttman, 1982)) WHAT ARE WORK VALUES?

14. DEFINING WORK VALUES TWO BASIC FACETS: FACET A- MODALITY OF OUTCOME a1 material or instrumental (pay, benefits) a2 social, affective (colleagues, esteem) a3 personal, cognitive, (ach., interest)

15. WORK VALUES FACET B– SYSTEM-PERFORMANCE CONTINGENCY. b1 system rewards, unrelated to performance (benefits, hours) b2 rewards contingent upon performance (pay, recognition)

16. Mapping sentence of Personal Values in various Life Areas

17. SSA of Personal Values

18. Intelligence Exercise Define in your own words the term: intelligence Propose tasks/tests to measure intelligence

19. Cartesian space of intelligence InferenceApplicationRecallTask Material Spatial Verbal Numerical

20. Intelligence – Mapping Sentence {recall} Testee (x) performs a task requiring the {application} {inference} of an objective rule concerned with {verbal} material {spacial} {numerical}  {very correct} { : } performance {very incorrect

21. Similarity structure Analysis (SSA) structural analysis/ small space analysis SSA space – geometric representation of the abstract content universe Assumption: every item can be represented by a point in the space, and every point can represent specific item The distance between the points is inversely related to the relations between the items. The higher the correlations the smaller the distance, and vice versa.

22. Achievement Motive Fist observed by projective techniques Thematic Apperception Test (TAT) David McClelland Limitations: Reliability – low Consider as uonitary concept Defining the Facets of Achievement Motive

24. Organizational Culture and IT The assessment of employee (x) of the A – Behavior Modality a1( Cognitive (belief a2( Affective (satisfaction a3( Instrumental (action a4 (Value (importance a5( Norm (desired behavior by B – Referent b1 Employee b2 Colleagues b3 Supervisor b4 Management Toward C- Objects c1 Work c2 IT High IT Usage Low } } { { } { { }

25. The Empirical Structure of the Behavior toward Work (Creativity). A Two Dimensional SSA, separation index= 0.95, coefficient of alienation = 0.14

26. The Empirical Structure of the Behavior toward IT. A Two Dimensional SSA, separation index= 0.88, coefficient of alienation = 0.05

27. The Empirical Structure of the Behavior Toward Work and IT. A Two Dimensional SSA, coefficient of alienation = 0.17