Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data -...

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Sociology 690 Unobtrusive Measures

Transcript of Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data -...

Page 1: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

Sociology 690

Unobtrusive Measures

Page 2: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

Data sources – Four alternatives

C. Make up the data - Simulation

D. Use another’s Data - Existing Data

A. Ask Someone Directly – Survey Research

B. Ask Someone else to Report - Observation

I. Reactive Measures (Potential for Hawthorne Effect)

II. Non-Reactive Measures (Unobtrusive data )

Page 3: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

I. Simulation

Unobtrusive / Non-Reactive Measures

Definition – A model or representation of a process involving: 1) a definition of the components; 2) their relationship; and 3) the realization of an outcome.

Involves three contexts in which data is generated: 1) Pure Machine; 2) Person-Machine; and 3) Pure Person..

Generally used when: 1) Time frame is restricted; 2) the Scope is too broad; or 3) there are ethical considerations

Page 4: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

C. Pure-Person

A. Pure Machine

Simulation – Types

The computer creates both the independent and dependent variables by: 1) making assumptions; 2) specifying a functional relationship; and 3) calculating their outcomes. Also known as Math Modeling.

B. Person-Machine The computer creates the the independent variable while the person responds, thereby creating the dependent variable. Also known as Computer Mediated Simulation.

The persons involved create both the independent and dependent variables through contingent interaction. Also known as Game Theory.

Page 5: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

Pure Machine - Types

There are three criteria by which to categorize machine models:

1. Deterministic vs. Probabilistic

2. Static vs. Dynamic

3. Discrete vs. Continuous

Are we analyzing all or some of the elements?

Is the measurement happening once or over time?

Is the measurement whole numbers or include fractions?

Page 6: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

Pure Machine Example - Graph Theory

In graph notation, the circles are people and the arrows are relationships (one direction for asymmetric relations, double headed for reciprocal relations).

The matrix reflects the graph in that the rows are the choosers and the columns are those chosen; there is a 1 present if the relation exists, 0 otherwise.

A mutual choice pair matrix can be obtained easily via computer by multiplying the matrix times its transpose (the matrix rotated 90 degrees). This can be further multiplied to obtain all three-way mutual choices-the typical minimum definition for a “clique in social groups.

0 1 1 0 0

1 0 1 0 0

1 1 0 1 0

0 0 1 0 1

0 0 0 0 0

Sociomatrix (A)

0 1 1 0 0

1 0 1 0 0

1 1 0 1 0

0 0 1 0 0

0 0 0 0 0

Sociomatrix (A x A’)

Page 7: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

Pure-Person Example – Game Theory

I. Zero-sum Games

II. Non-Zero-sum Games

A. Cooperative

B. Non-Cooperative (Prisoner’s Dilemma)

- One’s gain is another’s loss

- Joint gains and losses

Types

Page 8: Sociology 690 Unobtrusive Measures. Data sources – Four alternatives C. Make up the data - Simulation D. Use another’s Data - Existing Data A. Ask Someone.

Pure-Person Example – Prisoner’s Dilemma

The Definition is: 1) T>R>P>S and 2) 2R>T+S>2P The name comes from the best individual outcome being in direct conflict with best collective outcomes

Here the individual and collective outcomes are the same; that is, both cooperate. Hence there is no dilemma. This is a non-zero sum cooperative game.

These numbers reflect the prisoner’s dilemma described above. Because the individual and collective motive are in conflict, we call this a mixed motive or non-zero-sum non-cooperative game.

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Unobtrusive Measures – Existing Information

I. Secondary Analysis

Public Sources – Bureau of Census

Private Sources – ICPSR

II. Content Analysis - Text Based

- Data Based

Public Sources – Thomas

Private Sources – DataWarehouse