LEGAL NARRATIVE IN THE CITIZENS’ PANEL: IDENTIFYING THEORIES TO EXPLAIN STORYTELLING IN A SMALL GROUP DELIBERATION ABOUT BALLOT INITIATIVES

Robert C. Richards, Jr.

The Pennsylvania State University

Department of Communication Arts & Sciences

Presentation at National Communication Association, November, 2012

Overview• Three Theories of Legal Narrative

• The Oregon Citizens’ Initiative Review

• Methodology

• Four Results

• Conclusion

Three Theories of Legal Narrative

• Bennett and Feldman’s Storytelling Theory

• Pennington and Hastie’s Story Model of Juror Decision Making

• Sunwolf’s Decisional Regret Theory

The Oregon Citizens’ Initiative Review

• Public deliberation by a random sample of 24 citizens on a ballot initiative; analysis is published in official voters’ guide

• In 2010 two measures: (1) Mandatory Minimums, and (2) Medical Marijuana Dispensaries

Methodology

• Qualitative content analysis

• Original coding scheme

• Developed from prior study of government lawyers

• Limitations

Main Results

1. Narrative frequency

2. Counterfactual narratives

3. Policy effects as a narrative topic

4. Anticipated regret as a motivation for storytelling

1. Citizens Use Narrative Frequently to Discuss Legal Aspects of Ballot Measures

“…so I don’t see any reason why a person couldn’t go in one day and buy some [medical marijuana], go in the next day and buy some to sell to his friends and I have seen no evidence anywhere that any state has tried to prevent that from happening”

Frequency of Appearance of Narrative Thought Units in Transcripts of Citizens’ Deliberations During 2010 Oregon Citizens’ Initiative Review

Mandatory Minimums Medical Marijuana

Types of Narrative Thought Units

Number of Instances

Percentage of All

Instances

Number of Instances

Percentage of All

Instances

All Types of Thought Units

454 13% 1031 12%

Counterfactual Thought Units

260 8% 827 10%

Co-Created Thought Units

61 2% 152 2%

Responsive Thought Units

23 1% 75% 1%

Note. Mandatory Minimums: n=3447. Medical Marijuana: n=8377. Instances are thought units

2. Counterfactual Narratives Make Up a Large Share of All Narratives

• Speaker 1: “Because if you read it, it says you can be a repeat offender if you get caught doing one thing, but they file three charges on you, you're automatically a repeat offender. So, in reality you've had one run-in with the law, but –”

•  • Speaker 2: “But they really got mad at you.”•  • Speaker 1: “But they got really mad at you and you can

be buried because of that one time.”

Frequency of Appearance of Narratives in Transcripts of Citizens’ Deliberations During 2010 Oregon Citizens’ Initiative Review

Mandatory Minimums Medical Marijuana

Type of Narrative

Number of

Instances

Percentage of All

Instances

Number of Instances

Percentage of All

Instances

All Types 72 100% 191 100%

Counterfactual 51 71% 148 77%

Co-Created 14 19% 25 13%

Responsive 4 6% 12 6%

Note. Mandatory Minimums: n=72. Medical Marijuana: n=191. Instances are narratives

3. Negative and Indirect Policy Effects Are Major Topics of Narrative

“If you had six pounds of marijuana on you and you were licensed to transport it from the grower to the distributor, but you’re going down to Portland to sell it to dealers on the street and they pull you over, you can say, I have six pounds. How does the police know that it’s not going where it’s supposed to go?”

Frequency of Appearance of Topical Codes in Narratives, in Transcripts of Citizens’ Deliberations During 2010 Oregon Citizens’ Initiative Review

Mandatory Minimums Medical Marijuana

Code Number of Instances

Percentage of All Instances

Code Number of Instances

Percentage of All Instances

Policy Effects (Indirect)

15 21% Facts 16 8%

Fiscal Effects 8 11% Policy Effects (Negative Consequences)

15 8%

Policy Effects (Negative Consequences)

8 11% Policy Issues 15 8%

Note. Mandatory Minimums: n=72. Medical Marijuana: n=191. Instances are narratives

4. Anticipated Regret Is Among the Most Common Motivations for Narrative

• “I mean the treatment helps some people. And if they take it away from this, which is this is where it comes from; the first time offenders become repeat offenders because there would be no treatment program for them”

Frequency of Appearance of Motivational Concepts in Narratives, in Transcripts of Citizens’ Deliberations During 2010 Oregon Citizens’ Initiative Review

Mandatory Minimums Medical Marijuana

Concept Number of Instances

% of All Instances

Concept Number of Instances

% of All Instances

Anticipated Regret

23 32% Sharing Information

60 31%

Seeking Information

19 26% Anticipated Regret

50 26%

Sharing Information

15 21% Evaluating Laws

45 24%

Note. Mandatory Minimums: n=72. Medical Marijuana: n=191. Instances are narratives

Conclusion

• Sunwolf’s Decisional Regret Theory fits many (but not all) of these narratives

• Within the Oregon CIR, the citizen-lawmaker has the attributes of a realist

• The paucity of mentions of policy objectives in narratives suggests that citizens may use different discursive modes for different topics and functions

• We need to consider other theories or develop a new one

What’s Next?

• Validate the coding scheme and perform reliability tests on coding of 2010 Oregon Citizens’ Initiative Review transcripts

• Conduct a study applying Sunwolf’s Decisional Regret Theory to narratives from the Oregon Citizens’ Initiative Review

• Develop a theory that can account for all of the functions of and motivations for narrative observable in the 2010 Oregon Citizens’ Initiative Review

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Acknowledgements

• Grateful thanks to:• Professor Dr. John Gastil of The Pennsylvania State University

Department of Communication Arts & Sciences• Katherine R. Knobloch of the University of Washington Department

of Communication• Dr. Ekaterinia Loukianova of the Kettering Foundation• David Brinker of The Pennsylvania State University Department of

Communication Arts & Sciences

Contact

• Robert C. Richards, Jr., JD, MSLIS, MA, BA

• PhD Candidate• The Pennsylvania State University Department of Communication

Arts and Sciences• Email: rcr5122@psu.edu• Web: http://legalinformatics.wordpress.com/about/