# Interveners

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globals [num-adopted num-implementers] turtles-own [power attitude norm control intent last-attitude last-norm last-control last-intent implementer avg-advice-attitude avg-influence-attitude avg-interveners-influence] directed-link-breed [advice-ties advice-tie] directed-link-breed [influencer-ties influencer-tie] directed-link-breed [intervener-ties intervener-tie] to setup ca ;; make sure the input number of turtles is integer if num-turtles != floor(num-turtles) [set num-turtles floor(num-turtles)] ;; create turtles and distribute them crt num-turtles [ ;; color turtles blue - not adopted set color blue setxy random-xcor random-ycor set shape "person" set size 0.75 ;; this makes it easier to see ;; set intent levels based on survey data let u1 random-float 1 if u1 < 0.09 [set intent 1] if u1 >= 0.09 and u1 < 0.11 [set intent 2] if u1 >= 0.11 and u1 < 0.18 [set intent 3] if u1 >= 0.18 and u1 < 0.24 [set intent 4] if u1 >= 0.24 and u1 < 0.36 [set intent 5] if u1 >= 0.36 and u1 < 0.60 [set intent 6] if u1 >= 0.60 [set intent 7] ;; set attitude levels based on survey data let u2 random-float 1 if u2 < 0.002 [set attitude 1] if u2 >= 0.002 and u2 < 0.008 [set attitude 2] if u2 >= 0.008 and u2 < 0.03 [set attitude 3] if u2 >= 0.03 and u2 < 0.1 [set attitude 4] if u2 >= 0.1 and u2 < 0.25 [set attitude 5] if u2 >= 0.25 and u2 < 0.54 [set attitude 6] if u2 >= 0.54 [set attitude 7] ;; set norm levels based on survey data let u3 random-float 1 if u3 < 0.02 [set norm 1] if u3 >= 0.02 and u3 < 0.04 [set norm 2] if u3 >= 0.04 and u3 < 0.08 [set norm 3] if u3 >= 0.08 and u3 < 0.18 [set norm 4] if u3 >= 0.18 and u3 < 0.34 [set norm 5] if u3 >= 0.34 and u3 < 0.63 [set norm 6] if u3 >= 0.63 [set norm 7] ;; set control levels based on survey data let u4 random-float 1 if u4 < 0.11 [set control 1] if u4 >= 0.11 and u4 < 0.19 [set control 2] if u4 >= 0.19 and u4 < 0.27 [set control 3] if u4 >= 0.27 and u4 < 0.40 [set control 4] if u4 >= 0.40 and u4 < 0.57 [set control 5] if u4 >= 0.57 and u4 < 0.80 [set control 6] if u4 >= 0.80 [set control 7] ;; set implementer status based on survey data let u5 random-float 1 ifelse u5 < 0.47 [set implementer true set color green] [set implementer false] set num-implementers count turtles with [color = green] ] ask turtles [ ;; create the two types of ties randomly, according to the density of the original network ;; use a poisson distribution to represent a power-law type distribution of degree ;; this is done in a separate loop so all ties are possible create-advice-ties-to n-of (random-poisson (10.52 * num-turtles / 9799)) other turtles [set color yellow set thickness -0.5] create-influencer-ties-to n-of (random-poisson (2.12 * num-turtles / 9799)) other turtles [set color pink set thickness -0.5] ] set num-adopted 0 ;; create interveners who can influence the government agents. these new turtles will exert their influence ;; on the other turtles to try to create change crt num-interveners [ set color violet set shape "person" setxy random-xcor random-ycor ;; influencers own a "power variable," which effectively measures their ability to influence someone set power 1 + random 6 ;; they only have ties to potential implementers create-intervener-ties-to n-of num-intervener-ties turtles with [color = green] ] reset-ticks end to go if not any? turtles with [implementer = true and color = green] [stop] if ticks > 200 [stop] ask turtles [ ;; create the mean values of their neighbors attitudes; we differentiate between ;; advice ties and influencer ties ;; by initializing this way, the values won't change when turtles update their ;; properties let advice-attitude [] ask out-advice-tie-neighbors [set advice-attitude lput attitude advice-attitude] if not empty? advice-attitude [set avg-advice-attitude mean(advice-attitude)] let influence-attitude [] ask out-influencer-tie-neighbors [set influence-attitude lput attitude influence-attitude] if not empty? influence-attitude [set avg-influence-attitude mean(influence-attitude)] ;; save the average influence power of any turtle that is an interventionist let interveners-influence [] ask out-intervener-tie-neighbors [set interveners-influence lput power interveners-influence] if not empty? interveners-influence [set avg-interveners-influence mean(interveners-influence)] ;; save the current status of beliefs for use later set last-attitude attitude set last-norm norm set last-control control set last-intent intent ] ask turtles [ ;; if they have not already adopted, adjust their belief systems if (color = blue) or (color = green) [ change-attitude ;; update attitudes change-norm ;; update normative beliefs change-control ;; update perceived control change-intent ;; update intent ;; if they have the ability to implement, make change if intent and ability ;; are present if implementer = true [make-change] ] ] ;; interventionists can change their influence ties if their target has adopted ask turtles with [color = violet] [ ] set num-adopted count turtles with [color = red] tick end to change-attitude ;; attitude is positively influenced by norms and perception of control ;; this is programmed so that if norms or controls are more than attitude, attitude will increase, and vice-versa ;; I divided by 12 so that the max change is 1 unit, and multiplied by a random number so that the increase is further surpressed ;; (change will range from 0 to 1 (plus/minus) ;; I also cap the values at 1 to 7 set attitude (last-attitude + (random-float 1.0) * (norm/control-attitude * (last-norm - last-attitude) + (2 - norm/control-attitude) * (last-control - last-attitude)) / 12) if attitude > 7 [set attitude 7] if attitude < 1 [set attitude 1] end to change-norm ;; norm is positively influenced by attitudes and perception of control ;; this is programmed so that if attitudes or controls are more than norms, norms will increase, and vice-versa ;; perception of norms is also influenced by the attitudes of those in the advice/influence network. in other words, if people you ;; get advice from have a positive attitude, that should positive influence your attitude and vice-versa ;; I divided by 24 so that the max change is 1 unit, and multiplied by a random number so that the increase is further surpressed ;; (change will range from 0 to 1 (plus/minus) ;; I also cap the values at 1 to 7 set norm (last-norm + (random-float 1.0) * (control/attitude-norm * (last-attitude - last-norm) + (2 - control/attitude-norm) * (last-control - last-norm) + advice/influence-norm * (avg-advice-attitude - last-norm) + (2 - advice/influence-norm) * (avg-influence-attitude - last-norm)) / 24) if norm > 7 [set norm 7] if norm < 1 [set norm 1] end to change-control ;; perception of control is positively influenced by norms and attitudes ;; this is programmed so that if norms or attitudes are more than perceived control, control will increase, and vice-versa ;; I divided by 12 so that the max change is 1 unit, and multiplied by a random number so that the increase is further surpressed ;; (change will range from 0 to 1 (plus/minus) ;; I also cap the values at 1 to 7 set control (last-control + (random-float 1.0) * (influencer-control * avg-interveners-influence / 7) + (random-float 1.0) * (attitude/norm-control * (last-attitude - last-control) + (2 - attitude/norm-control) * (last-norm - last-control)) / 12) if control > 7 [set control 7] if control < 1 [set control 1] end to change-intent ;; intent is positively influenced by all of attitudes, norms, and perceived control ;; I divided by 18 so that the max change is 1 unit, and multiplied by a random number so that the increase is further surpressed ;; (change will range from 0 to 1 (plus/minus) ;; I also cap the values at 1 to 7 set intent (last-intent + (random-float 1.0) * ((2 - influencer-control) * avg-interveners-influence / 7) + (random-float 1.0) * ( attitude-intent * (last-attitude - last-intent) + norm-intent * (last-norm - last-intent) + (3 - attitude-intent - norm-intent) * (last-control - last-intent)) / 18) if intent > 7 [set intent 7] if intent < 1 [set intent 1] end to make-change ;; to make adoption "hard", I incorporated what effectively functions as a threshold ;; in other words, change can only occur if someone perceives themselves to have high control, and have high intent ;; then, there is still a random component; the number 0.5 is meant to create randomness if control >= control-threshold [ if intent >= intent-threshold [ if random-float 1 < 0.5 [set color red] ;; indicate adoption via changing the color ] ] end

There are 2 versions of this model.

## Attached files

File | Type | Description | Last updated | |
---|---|---|---|---|

AaronSchecter_June1.docx | word | Project Update 3 | about 4 years ago, by Aaron Schecter | Download |

Interveners.png | preview | Image | about 4 years ago, by Aaron Schecter | Download |

**Parent:** Adoption of Health Practices in Rural India

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