Mark Gibson - Compliance Presentation
•Download as PPTX, PDF•
1 like•1,149 views
A brief presentation I gave to introduce a discussion session at the ICES BehavFish Working Group. For more information, see the associated blog post at www.breachingtheblue.com
Recommended
More Related Content
Similar to Mark Gibson - Compliance Presentation
Similar to Mark Gibson - Compliance Presentation (19)
Recently uploaded
Recently uploaded (20)
Mark Gibson - Compliance Presentation
- 1. Can we come up with proposals to increase fisher compliance? BehavFish Workshop ICES, Copenhagen October 22, 2014
- 2. Fisheries Management is People Management Diverse Actors Diverse Motivations Diverse Methods Diverse Fishery Structures
- 3. Compliance “the degree to which the actions of an individual, or group of individuals, accord with the rights and rules to which they are bound”
- 4. Common Rule Types Access Area Gear Capacity Time Catch Effort Reporting
- 5. Prevalence Illegal and unreported fishing accounts for between 11 and 26 million tonnes annually. The total value estimated to be between $10 bn and $23.5bn annually Agnew, D.J., J. Pearce, G. Pramod, T. Peatman, R. Watson, J.R. Beddington, and T.J. Pitcher. 2009. Estimating the worldwide extent of illegal fishing. PLOS ONE, 4 (2):e4570
- 6. Compliance Theory Rational Choice E.g. Gary Becker (1968) Right Realism E.g., Situational Crime Prevention Behavioral Economics E.g. Dan Ariely (2013) Irrational Realism?
- 7. “Everybody Cheats” Self-Concept Maintenance Theory It would suggest that: Most illegal fishing is conducted not by specialized, economically rational criminals, but by ordinary fishers that cheat by just a little. Fisheries managers should begin to consider the “irrational” or non-economic factors affecting illegal fishing to better preserve their resources.
- 8. Fishers Cheat More? Non-monetary Assets Organization Revenge Mental Depletion
- 9. Opportunities Revenge Mental Depletion In-Group Contagion/Desistance Out-Group Desistance Snowballing/Slippery Slope
- 10. Measuring Effectiveness Direct Observer program/EMS – costly At-sea Inspections – Nonrandom, costly Dockside Inspections – Limited detection, nonrandom AIS/VMS – Limited detection of offenses Indirect Logbooks & Catch Reports – Potentially Biased Supply Chain Audits – institutionally limited Noncompliance Risk Perception? Contagion False Consensus Effect
- 11. Case Study Australian Fisheries Management Agency’s “show cause” model for closed areas “Since its commencement, in June 2010, the program has resulted in a reduction in the number of suspected closure breaches of 87% over the first three months and an overall reduction of over 94%” Arguably no new costs/risks were imposed on fishing operations The Supervision Effect?
Editor's Notes
- Actors: captains, crew, vessel owners, processors Motivations: subsistence, livelihood, profit, recreation, culture Methods: vessel-based (e.g., trawl, longline), shore-based Structures: small-scale, artisanal, industrial, vertically-integrated, multiple vs. single landing points, transhipments
- These rules are also employed to meet various objectives: sustainability, conflict reduction, profit maximization, etc.
- The FAO reported marine catches for 2009 of 79.9 million tonnes. This means that illegal and unreported fishing accounts for between 12 and 25 percent of the world marine catch!
- Right realism recognizes that rational choice is imperfect, but “good enough” and attempts to provide recommendations on the base of rational choice theory that are sufficiently specific to be implemented and tested. Situational crime prevention has been defined as "the use of measures directed at highly specific forms of crime, which involve the management, design or manipulation of the immediate environment in as systematic and permanent a way as possible" (Clarke & Hough: 1980). Five types of actions: increase effort, increase risks, reduce rewards, reduce provocations, remove excuses Dan Ariely – The Honest Truth about Dishonesty. Perhaps we might similarly hope for a pragmatic application of behavioral economics, even as we recognize that it is imperfect.
- Mazar, N., Amir, O., & Ariely, D. (2008). The dishonesty of honest people: A theory of self-concept maintenance. Journal of marketing research, 45(6), 633-644.
- Research suggests it is easier to steal non-monetary items. For example, that it would be easier to “borrow” a $1 pen you found on the floor of your friend’s apartment rather than a $1 bill. Similarly, research suggests we can rationalize cheating when we think it is is for others (like our crew mates?), or to apply retributive justice. Finally, it is clear that we can cheat as a way to ease our mental burdens, perhaps such as the navigating of complex fisheries regulation, or making it through grueling fishing trips?
- It is likely that revenge and mental depletion could be addressed with policy modifications. Meanwhile, research also suggests that there are other aspects more general to all “cheating” behavior that can be addressed with government policy. For instance, if you think If everyone is breaking the rules, what do you do? Take a stand at your own loss? But what happens when you see that someone clearly could have done something “selfish” and desists? Role models matter. Similarly, if we are wired or socialized to think our community is better than others, the bad behaviors of “strangers” (whether real or otherwise) can inspire us to do better. Finally, as the Milgram experiments showed, one bad decision can provide the grease for more bad decisions.
- A methodological challenge should be considered along with our specific proposals for improving compliance. How do we measure the effectiveness of a compliance intervention? I’d argue this is a problem that hasn’t been adequately considered before. For example, the FAO recognizes the monitoring of compliance as a key element of fisheries management, yet in all its years has never provided technical guidance on how to measure it. One measure I see as potentially useful would be a survey where we gauge fisher perceptions of noncompliance. While it could probably never be used to get an accurate reading of the true state of compliance in a fishery, it would still be highly meaningful. Two reasons. First, we base our behavior on that of others, so if we think everyone is cheating…what do we do? Second, a recognized cognitive bias/heuristic is that we assume others behave as we do (false consensus effect), so when we try to imagine what others do, we base it on our own behavior. Thus, a perception survey could entail some degree of informing on actual behavior.
- Model designed to show: that AFMA analyses the VMS on a regular basis that the onus is on the operator to explain suspect activity that AFMA reserves the right to take enforcement action that non compliance to closures is likely to be detected Read the full example here: http://www.afma.gov.au/managing-our-fisheries/compliance-activities/the-domestic-compliance-program/