communicating research findings more effectively: the potential for conflict index jerry j. vaske...

Communicating Research Findings More Effectively:

The Potential for Conflict Index

Jerry J. VaskeColorado State University

Human Dimensions of Natural ResourcesFort 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

• ChallengeEffectively communicating the meaning of abstract statistics (e.g., standard deviation, standard error)for measuring consensus

• Solution – Potential for Conflict Index (PCI)Manfredo, Vaske, & Teel, 2003Vaske 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

-3 -2 -1 0 1 2 3

HighlyUnacceptable

ModeratelyUnacceptable

SlightlyUnacceptable

Neutral SlightlyAcceptable

ModeratelyAcceptable

HighlyAcceptable

• 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. Vaske 1

Mark D. Needham 2

Lori B. Shelby 1

Caroline Hummer 1

1 Colorado State University2 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

Management Action Highly Unacceptable Unacceptable

SomewhatUnacceptable Neither

Somewhat Acceptable Acceptable

Highly Acceptable

Monitor the situation -3 -2 -1 0 1 2 3

Frighten the bear away -3 -2 -2 0 1 2 3

Capture and relocate the bear -3 -2 -1 0 1 2 3

Destroy the bear -3 -2 -1 0 1 2 3

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.

Traditional Display

Descriptive Statistics – Acceptability of Destroy Animal

Mean Std Error Std. Dev. Variance Skewness Kurtosis

Raccoon roaming neighborhood -2.47 .114 1.229 1.510 2.554 6.075

Raccoon pest -2.09 .152 1.643 2.700 1.836 2.339

Raccoon kills humans 1.16 .202 2.185 4.775 -.862 -.740

Bear roaming neighborhood -2.58 .096 1.036 1.073 3.251 11.618

Bear pest -2.30 .120 1.295 1.677 2.127 4.390

Bear kills human .17 .203 2.190 4.798 -.202 -1.355

Mt Lion roaming neighborhood -2.41 .126 1.366 1.865 2.598 6.268

Mt Lion pest -2.10 .148 1.599 2.558 1.996 3.164

Mt Lion kills human .18 .212 2.279 5.193 -.124 -1.501

Acceptability of Destroying AnimalHighly

Acceptable

Neither

Highly Unacceptable

Raccoon

Presence Nuisance Kills Human

.05 .04.08

.14 .13

.36

.58

.06

.63

-3

-2

-1

0

1

2

3

Bear Mountain Lion

Larger bubbles reflect more potential for conflict

Other Applications of PCI

0.70

0.19

0.080.05

0.21

0.60

0.85

VeryAcceptable

Neutral

VeryUnacceptable

Acc

epta

bili

ty

Level of Flow (CFS): 5000 8000 10000 15000 30000 40000 50000

-3

-2

-1

0

1

2

3

Acceptability of Instream FlowsAcceptability of Instream Flows

Chronic Wasting Disease Management

Highly Acceptable

Neither

Highly Unacceptable

.05Continue to test

deer / elk for CWD

.12No action – allow CWD to

take its natural course

.62Use trained agency staff to dramatically reduce herds

in affected zones

Use hunters to drama-tically reduce herds in

affected zones

.26

Act

ion

Acc

epta

bilit

y

-3

-2

-1

0

1

2

3

Highly Acceptable

Neither

Highly Unacceptable

Act

ion

Acc

epta

bili

ty

Injures Person

KillsPerson

Kills Pet

Seenin Area

Acceptability of Destroying Lion by Attitude

Negative Attitude

.61

.07

Positive Attitude Neutral Attitude

.20

.42

.14

.41.31

.68

.21 .19

.41

.09

-3

-2

-1

0

1

2

3

Take away permit for year

Take away permit for

15 days

Give a fine

Do nothing

San

ctio

ns

Fishing inNo-take

zone

Illegal fishing

methods

Off-seasonSea cucumber

harvest

Off-seasonlobsterharvest

Shark harvest

Fishing Violations

Norms for Fishing Violations in the Galapagos

3

2

1

0

Santa Cruz Isabela

.62 .63

.66.62 .74

.53 .53

.56 .55 .74

Take away permit for year

Take away permit for

15 days

Give a fine

Do nothing

San

ctio

ns

Fishing inNo-take

zone

Illegal fishing

methods

Off-seasonSea cucumber

harvest

Off-seasonlobsterharvest

Shark harvest

Fishing Violations

Norms for Fishing Violations in the Galapagos

Santa Cruz Isabela

3

2

1

0

Par or lower Above Par

Satisfaction with Golfing by ScoreDelighted

Pleased

MostlySatisfied

Mixed

MostlyDissatisfied

Unhappy

Terrible

OwnPerformance

CourseCondition

Pace of Play

Satisfaction with Occupation Therapy Treatments

Care giversPatients

ExtremelySatisfied

Unsure

ExtremelyDissatisfied

In-patient Out-patient In-home

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 ...

-3 -2 -1 0 1 2 3

HighlyUnacceptable





HighlyAcceptable

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)

-3 -2 -1 0 1 2 3

HighlyUnacceptable





HighlyAcceptable

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

max

,2

dnnPCI hkhk

PCI2 in Excel5-point scale

# of respondents at: Value

-2 100

-1 0

0 0

1 0

2 100

Total sample 200

Total distance

Maximum distance

PCI

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

Toward a Validation of PCI2

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

PCI2 & Sample Size

7-point scale

0.479 0.48 0.485 0.486 0.489 0.492 0.493 0.495 0.496 0.497

5-point scale

0.351 0.349 0.349 0.351 0.351 0.351 0.351 0.35 0.35 0.35

Each estimated mean based on 1000 simulated samples

0

0.2

0.4

0.6

0.8

1

100 200 300 400 500 600 700 800 900 1000

Sample Size

PC

I V

alue

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/

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