Research Questions to Research Design Week 10

1. DEPARTMENT OF SOCIOLOGY
Research Questions to Research
Design (SY7034)
Edmund Chattoe-Brown
ecb18@le.ac.uk
Thursdays 1500-1700 (Brookfield 0.24)

2. WEEK 10

3. 1. Plan
• Administration.
• Experiments.
• Simulation: Overlap?
• Break.
• Social Networks: Overlap?
• Wrapping Up.

4. 2. Administration
• Registration.
• Book shortages reminder.
• https://leicester.onlinesurveys.ac.uk/sy70
34-research-questions-to-research-
design-2014
• 5 responses as of this morning!

5. 3. A simple experiment
• The “ultimatum game”.
• Two people/roles (one who offers, one who decides).
• Offer anything from £0.00 to £2.00 (and thus intend to keep
anything from £2.00 to £0.00)
• If decider refuses offer BOTH GET NOTHING.
• If decider agrees then division of £2.00 follows the offer.
• You will play 8 times.
• You will be given a letter (you are either “A” or “B”.)
• Afterwards, one pair (uniquely identified on A sheet) will get
their “splits” in real money.

6. 4. Practicalities
• Identifying players and pairs.
• Giving out and checking trial games.
• Giving out “real” games.
• Choosing winner (www.random.org) and
“paying off”.

7. 5. What’s my game?
• An “economic” experiment: You have to pay
people to motivate them “properly”.
• What is Rational Choice Theory? What does it
predict about offer and acceptance in the
ultimatum game?
• Here’s one I prepared earlier …

8. 6. Ultimatum Game Results 1
Average Difference From 50/50 Split in "Turns"
and "No Turns" Conditions ( N= 15)
0
10
20
30
40
50
60
1 2 3
1: Turns, 2: No Turns, 3: Rational Choice Prediction
Difference

9. 7. Ultimatum Game Results 2
Average Number of Rejections in "Turns" and "No
Turns" Conditions ( N= 15)
0
0.2
0.4
0.6
0.8
1
1.2
1.4
1.6
1.8
2
1 2 3
1: Turns, 2: No Turns, 3: Rational Choice Prediction
Rejections

10. 8. Thoughts on experiments
• Needs thought and preparation but doesn’t have to be fantastically
hard to organise.
• Good for testing clear theories.
• Can be very creative: How to experiment on “power” in the
laboratory?
• Quantitative rules apply: Can you “afford” a big enough sample if you
have to pay?
• How “artificial” is your experiment? Will it generalise outside the
laboratory? A trade off.
• Sociological “twists”: Play in pairs and record discussions for
qualitative analysis.
• How much ethical guidance did I break?

11. 8. Social networks
• Ethnography looks at “whole settings” using
narratives.
• Qualitative interviews look at individual accounts
using narratives.
• Surveys look at individual accounts using numbers.
• What have we missed? Relationships!
• How is that everyone can be unique while still
displaying regularities that sociology can discover?

12. 9. A picture is worth … thinking about
“To construct a
class
sociogram, ask
each pupil to
confidentially
list two
students to
work with on an
activity.”

13. 10. Core elements
• Nodes and relations: Here children in a class and work nominations.
• Different kinds of relations: a has been introduced to b implies b has been
introduced to a but a likes doesn’t imply that b likes a?
• Children vary in popularity: Some children only make “out” nominations.
• Children are strongly segregated into a boy’s group and a girl’s group
(although there are some ambiguous names.)
• Is Nick “big man on campus?”
• Is the girl’s network less hierarchical/more egalitarian? Evidence?
• How different is it to be Nick and Livie? What effects might that have?
• What might happen if Jo missed a month of school? Is there anyone in the
girl’s group with an equivalent position?
• What is special about Ann, Fleur and Meg?

14. 11. Collecting network data
• Sheets will be shredded directly after network
is constructed.
• Network will be presented anonymously: Can
you identify yourself?
• See accompanying brief description of the
network structure that will be posted on Bb.
• Compare with classroom network.

15. 12. Break
• 10 minute “comfort break”.

16. 13. Agent-based Modellling
• Is there anything else apart from narratives
and numbers we can build a research method
on?
• Yes, computer programmes. (You don’t need
to know the details any more than you do to
use SPSS – though you might do to use it
well.)
• Best just to show you, at least for now.

17. 14. Schelling Segregation Model
• I’m not presenting this because it represents social reality.
• “Agents” live on square grid: Each has maximum 8 neighbours.
• There are 2 “types” of agents (square/triangle). Some grid
spaces are vacant. Initially agents distributed randomly.
• All agents decide what to do in the same very simple way.
• Each agent has a preferred proportion (PP) of neighbours of its
own kind (0.5 PP means you want at least half your neighbours
to be your own kind - but you would accept all of them i. e. PP
is minimum.) Vacant grid spaces “don’t count” which is why the
PP is a fraction not a number.
• If an agent is in a position that satisfies its PP then it does
nothing otherwise it moves to a vacancy chosen at random.

18. 15. Initialisation
NetLogo

19. 16. PP=0.6

20. 17. PP=0.3

21. 18. PP=1

22. 19. “Computational experiments”
-20
0
20
40
60
80
100
120
0 50 100 150
%SimilarAchieved(Social)
% Similar W anted ( I ndividual)
I ndividual Desires and Collective
Outcomes
% similar
% unhappy

23. 20. Four reasons this really matters
• The micro-macro problem. What does qualitative
data add up to? What does quantitative data drill
down to? Intuitive reasoning “between” levels could
well be flawed.
• How would we make this a realistic model? ABM has
a distinct methodology with its own logic.
• If a system this simple has this “problem” imagine
how “bad” it is for realistic systems!
• To the man who has only a hammer … buffer zones,
clusters defined by their boundaries.

24. 21. Exercise 3 (10 minutes)
• What other research methods might deal with the
drawbacks of a survey or qualitative interviews about
rumours?

25. 22. Summing up
• Resounding silence?
• Ethics.
• Anything you don’t understand about assignment instructions
or anything not clear about them? (Not what do they say!)
• Actual research proposal questions.
• Issues arising from my “formative”.
• Reread/ask: Uh-oh!
• Check your problems: How much of the formative feedback
was not about your topic?
• Other?