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This presentation introduces the Potential for Conflict Index (PCI) and discusses enhancements in the 2nd generation of PCI. It provides a partial validation of PCI2 and demonstrates the PCI2 menu system. The goal is to effectively communicate research findings in a way that bears meaning on problems of managerial or scientific interest.
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Communicating Research Findings More Effectively: The Potential for Conflict Index Jerry J. Vaske Colorado State University Human Dimensions of Natural Resources Fort Collins, CO 80523
Overview of Presentation • Introduce Potential for Conflict Index (PCI1) • Describe enhancements in 2nd generation of PCI2 • Provide a partial validation of PCI2 • Demonstrate the PCI2 menu system
Goal – Challenge – Solution • Goal of Human Dimensions / Recreation research Conceptualize, measure and interpret variables and their relationships in a way that bears meaning on problems of managerial or scientific interest • Challenge Effectively communicating the meaning of abstract statistics (e.g., standard deviation, standard error)for measuring consensus • Solution – Potential for Conflict Index (PCI)Manfredo, Vaske, & Teel, 2003 Vaske et al., 2006; Vaske et al., 2010
Potential for Conflict Index (PCI) • Integrates into one measure information about: • Central tendency • Dispersion • Shape of a distribution • Uses graphic display: Easy interpretation • Places findings in managerial context(e.g., the acceptability of a given mgmt. action)
PCI1 Measurement Requirements Response scale • Balanced scale with equal number of response options on either side of “Neutral” point • Number of response options can be 3, 5, 7, or 9(typical to have 5 or 7 response options) • Numerical ratings must be assignedwith center point given value of 0
PCI Assumptions • Greatest potential conflict (PCI = 1) occurs with bimodal distribution: • 50% rate mgmt. action as “Highly Unacceptable” • 50% rate mgmt. action as “Highly Acceptable” • 0% are “Neutral” • No conflict (PCI = 0) occurs when: • 100% rate mgmt. action in a single category(e.g., 100% “Highly Unacceptable” OR 100% “Highly Acceptable”) • Index range: 0 (no conflict – most consensus) to 1 (most conflict – least consensus)
Previous Applications of PCI • Yellowstone wolf mgmt. (ID & WY) • Desert tortoise mgmt. (CA) • Chronic wasting disease (8 states) • Off leash dogs urban parks (CO) • Wildlife values (19 states) • Wildland fire management (3 states) • Instream flows in Hell’s Canyon (ID) • Scuba divers / snorkelers (FL) • Summer use – Whistler ski area (BC)
Different Species & Severity Human-Wildlife Interactions Jerry J. Vaske1 Mark D. Needham2 Lori B. Shelby1 Caroline Hummer1 1 Colorado State University 2 Oregon State University Paper presented at International Union of Game Biologists XXVIII Congress, Uppsala, Sweden, 2007
Survey scenarios manipulated 3 species: Raccoons, Bears, Mountain Lions 3 levels – Severity ofhuman-wildlife interaction: Presence, Nuisance, Kills human Example scenario: A person encounters a black bear in their neighborhood. The bear charges and mauls the person, resulting in the person’s death. Given this scenario, how unacceptable or acceptable would it be for wildlife agencies to take each of the following actions.
Highly Acceptable Neither Highly Unacceptable Nuisance Presence Acceptability of Destroying Animal Larger bubbles reflect more potential for conflict 3 2 .36 1 .58 .63 0 -1 -2 .14 .13 .06 .08 .05 .04 -3 Mountain Lion Raccoon Bear Kills Human
Very Acceptable Neutral Very Unacceptable Acceptability Acceptability of Instream Flows Level of Flow (CFS): 5000 8000 10000 15000 30000 40000 50000
Use hunters to drama- tically reduce herds in affected zones .05 .26 Continue to test deer / elk for CWD .62 Use trained agency staff to dramatically reduce herds in affected zones .12 No action – allow CWD to take its natural course Chronic Wasting Disease Management Highly Acceptable Neither Highly Unacceptable 3 2 1 Action Acceptability 0 -1 -2 -3
.09 .21 .19 .31 .41 .41 .61 .68 .42 .20 .14 .07 Negative Attitude Positive Attitude Neutral Attitude Acceptability of Destroying Lion by Attitude Highly Acceptable Neither Highly Unacceptable 3 2 1 Action Acceptability 0 -1 -2 -3 Seenin Area Kills Pet Injures Person KillsPerson
Norms for Fishing Violations in the Galapagos Take away permit for year Take away permit for 15 days Give a fine Do nothing 3 2 1 0 Sanctions Fishing in No-take zone Illegal fishing methods Off-season Sea cucumber harvest Off-season lobster harvest Shark harvest Fishing Violations Isabela Santa Cruz
Norms for Fishing Violations in the Galapagos Take away permit for year Take away permit for 15 days Give a fine Do nothing 3 2 1 0 Sanctions Fishing in No-take zone Illegal fishing methods Off-season Sea cucumber harvest Off-season lobster harvest Shark harvest Fishing Violations Isabela Santa Cruz
Satisfaction with Golfing by Score Delighted Pleased MostlySatisfied Mixed MostlyDissatisfied Unhappy Terrible OwnPerformance CourseCondition Pace of Play Par or lower Above Par
Satisfaction with Golfing by Score Delighted Pleased MostlySatisfied Mixed MostlyDissatisfied Unhappy Terrible OwnPerformance CourseCondition Pace of Play Par or lower Above Par
Care givers Satisfaction with Occupation Therapy Treatments ExtremelySatisfied Unsure Extremely Dissatisfied In-patient Out-patient In-home Patients
Care givers Satisfaction with Occupation Therapy Treatments ExtremelySatisfied Unsure Extremely Dissatisfied In-patient Out-patient In-home Patients
Care givers Satisfaction with Occupation Therapy Treatments ExtremelySatisfied Unsure Extremely Dissatisfied In-patient Out-patient In-home Patients
Enhancements in PCI2 • Generates statistic from SPSS, SAS, Excel & PHP • A simulation generates M & SD (default n = 400)(SD allows test of differences between PCI values) • Allows for: • different scale widths (2, 3, 4, 5, 6, 7, 8, 9) • unipolar & bipolar scales (with or without neutral value) • different power functions (i.e., 1, 2 or any power > 0) • different distance functions (D1, D2, D3)
PCI2 – Distance Based Formula • Consider person (x) response relative to person (y) • Responses = rx and ry • Distance between people dx,y = f(rx, ry) • Different ways to define distance: dx,y = |rx – ry| • Issue: People at –3 & –2 not really in conflict; differ only in degree to which views are held • Alternative distance formulations ...
PCI2 – Alternative Distance Functions D1 dx,y = (|rx – ry| – 1) If sign(rx) ≠ sign(ry); (e.g., rx = –3 & ry = +1) otherwise dx,y = 0 • Neutral is not considered in determining distance (D1: –3 to 1 is 3) D2 dx,y = |rx – ry| If sign(rx) ≠ sign(ry); otherwise dx,y = 0 • Neutral is considered in determining distance (D2: –3 to 1 is 4)
PCI2 Formula where: nk = number of respondents for each scale value nh = number of respondents at other scale values dk,h = distances between respondents δmax = maximum distance between extreme values * number of times this distance occurs
PCI2 in Excel 200 0 0 0 0 200 0 60000 0 50 50 0 50 50 200 40000 60000 .67 25 25 100 25 25 200 10000 60000 .17 10000 60000 1.00
Current Recommended Settings: PCI2 • Distance: D1 • Power: P1: Power = 1 • Scale width: 5 or 7 points • Recommendations subject to further testing and validationusing actual & simulation data
PCI2 – General Validation • Meets boundary conditions(i.e., PCI = 0 and / or 1 when it should) • Simulated values for a distribution are approximately normally distributed(i.e., usual tests for differences can be used) • Bias is small relative to standard deviation in a PCI estimated for a survey
1 0.8 7-point scale 0.6 0.495 0.496 0.497 0.492 0.493 0.489 0.485 0.486 0.479 0.48 PCI Value 0.4 0.351 0.349 0.349 0.351 0.351 0.351 0.351 0.35 0.35 0.35 0.2 5-point scale 0 100 200 300 400 500 600 700 800 900 1000 Sample Size Each estimated mean based on 1000 simulated samples PCI2 & Sample Size
PCI – Conclusions • PCI offers an intuitive approach to summarizing statistical results • Based on past experiences, managers understand PCI results • Computing PCI & graphical displayis straightforward • PCI2 allows for multiple analytical options & experimentation capabilities
PCI – Future Research • Continue validation • Further examination of scale width issues • Link PCI to practical significance indicators(e.g., effect sizes, Van der Eijk’s measure of agreement) • Apply PCI to more human dimensions issues • Develop standards for interpreting PCI values
Questions PCI2 SPSS, Excel, PHP, PowerPoint programs available at: http://welcome.warnercnr.colostate.edu/~jerryv/