Sexual Assault

1 collaborator

WHAT IS IT?

This model attempts to simulate sexual assault given statistically defined characteristics in certain environrments through a small isolated human population. It attempts to illustrate the positive effects of certain educational and empathy building policies to address the growing university problem.

It is known that sexual assault is a growing problem on university campuses all over the world. The statistics iterate that young first year or second year women are particular at target. Overall, 25% of women are thought to experience assault during their college years. In additoin to this, 60% of women generally choose not to tell anyone. University culture consists of heavy drinking, relative male hostility through fraternities, lack of sexual prevention education, and subjective empathy. Based on different enviornments that unversity students tend to interact in, this model focuses only on the sexual assault given the relatively similar characteristics of sexual assault cases in the respective environments.

This model examines the emergent effects with respect to 4 enviornments. These enviornments consist of bars, fraternities, school, and parks or open space.

The user controls the population with respect to females and males. The user can also control the impact of the characteristic traits to observe trends within the enviornment. Exploration of efforts or prevalence in educational prevention programs and empathy can exemplify how changes in policy can affect the rate of sexual assault, while observing the effects of lacks of policy.

By allowing the user to control the different characteristic traits of sexual assault as mentioned in literature, and efforts to combat the epdiemic, users can varying effects.

how often an average individual will choose to be tested, the user can explore an important dimension of HIV's threat to public health. Because the virus does not make itself immediately known in its host, individuals are often infected for some time before a test or immune deficiency symptoms (which leads to a test) identifies them as such. Regular identification of individuals infected by the virus could have significant public health impacts if knowledge of the infection positively affected sexual behaviors. This model explores this possibility by making all individuals who know of their positive HIV status always practice safe sex.

HOW IT WORKS

(what rules the agents use to create the overall behavior of the model)

The model uses males and females to represent interactions. Individuals are given personality characteristics (1/4 each preferred to a different enviornment). Individuals wander around the world fulfilling personality needs and interacting with females. Upon coming into radius with a suitable partner, there is a chance the female will be assaulted depending on the enviornment (characeristic traits in respect to sexual assault cases in these enviornmetns differ probabilites). For example, alcohol may highly influence assault in a bar wheras in a school it may not have an effect at all. When assault occurs, the assaulted female turns red.

The differences in the age of the population is represented by the colors of individuals. There are 4 colors used for each males and females. The older the male, the darker their tint of blue is. Freshmen thus are lightest blue and seniors the darkest. The same idea applies for females in respect to pink. The darker the pink, the older the female and the lighter the pink the younger she is. Freshmen females thus are the lightest pink and Seniors are depicted as dark pink. Red indicates that a female has been assaulted.

HOW TO USE IT

The SETUP button creates individuals with particular behavioral personalities. Patcehs are also set up with probability of assault tendencies given statistical literature supporting the role of specific factors in given enviornments. Accourding to the value of interface's five sliders, one can adjust the levels of traits (hostility, empathy, education, alcohol) to see differences in assault patterns. Once the simulation has been setup, you are now ready to run it, by pushing the GO button. GO then starts the simulation and runs it continuously until GO is pushed again. During a simulation initiated by GO, adjustments in sliders can affect the behavioral tendencies of the population. To observe full impacts, press SETUP again and observe from the beginning.

Monitors show the population that is assaulted by age and location (patch-area/enviornme nt).

Here is a summary of the sliders in the model. They are explained in more detail below.

men: How many men simulation begins with.
women: How many women simulation begins with.
hostility: General level of how impactful hosility that is taken into account for assault (0--10).
alcohol: General level of how impactful alcohol that is taken into account for assault (0--10).
empathy: General level of how impactful empathy intervention that is taken into account for assault (0--10).
education: General level of how impactful educational prevention intervention that is taken into account for assault (0--10).

The total number of individuals in the simulation is controlled by the slider men and women (initialized to vary between 0--100), which must be set before SETUP is pushed.

During the model's setup procedures, all patches are given probabilities for assault according to four additional sliders and statistical weights of characteristic traits of sexual assault.

The slider hostility (0--10) determines the impact of hostile behavior of the male turtles in assaulting the female turtles. When the hostility slider is set at zero, assault is at baseline, although (because probailities are chance) assault is still possible.

The slider alcohol determines how much of a role alcohol plays in assault given the enviornmental sexual assault characteristic probabilities. Again, the tendencies of both individuals in a relationship are considered; the relationship only lasts as long as is allowed by the tendency of the partner with a shorter commitment tendency. When the alcohol slider is set at zero, assault is at baseline, although (because probailities are chance) assault is still possible.

The slider empathy (0--10) determines the level of empathy that is factored in a males probability to assault. If a higher empathy is indicated, it should be apparent that assault in respect to the female population is largely elongated due to the fact that empathy has a statistically proven positive effect in mitigating sexual assault.

The slider education (0--10) is the final slider of the interface. It determines the determines the level of education that is factored in a males probability to assault. Education has a statistically effective rate (almost 50%) in mitigating assault. If a higher rate of education intervention is indicated, it should be apparent that assault in respect to the female population is largely elongated due to the effect of education on assault.

The model's plot shows the total number females assaulted, females assaulted by age, and various locations of assaults.

THINGS TO NOTICE

(suggested things for the user to notice while running the model)

Play with the intial men and women population to oberve the rates of asault when there are both fewer men than women and vice versa.

Adjust the characteristic traits of sexual assault to see how quickly rates increase in freshmen and sophomores, more quickly than the other populations.

Adjust hosility to observe the locations of where most assaults take place. Do this same thing with education and empathy and you can see some clear trends.

The overall rate of assault amongst females and their locations is deeply effected by increasing instigators of sexual assault and are intersingly affected whilst observing the impact of certain preventative measueres.

THINGS TO TRY

(suggested things for the user to try to do (move sliders, switches, etc.) with the model)

Run some experiments with the GO button to find out the effects of different variables on assault with respect to females. At what rate is abuse in the female turtles affected with full educational programmes?

Are the effects of some mitigating slider variables to sexual assault mediated by the effects of others? What are the best measures to best decrease rates of sexual assault.

EXTENDING THE MODEL

Much like all computer simulations of human behaviors, this model has necessarily simplified its subject area substantially. The model therefore provides numerous opportunities for extension:

Perhaps the implementation of more personality based traits amongst females.

Introduction of more intelligent agent behavior (females looking out for each other to resemble the buddy system)

The effect of socioeconomic status and poverty to sexual assault.

Allow repeated instances of assault to observe traits that are difficult to address. This can help create more well rounded prevention strategies.

NETLOGO FEATURES

(interesting or unusual features of NetLogo that the model uses, particularly in the Code tab; or where workarounds were needed for missing features)

RELATED MODELS

(models in the NetLogo Models Library and elsewhere which are of related interest)

CREDITS AND REFERENCES

(a reference to the model's URL on the web if it has one, as well as any other necessary credits, citations, and links)

Comments and Questions

Please start the discussion about this model! (You'll first need to log in.)

Click to Run Model

extensions [table]

globals [bar school park frat assault-place-count]

turtles-own [
  dict
education? ;; education personality variable that is able to be manipulated.
sex ;; to designate male and female interactions and procedures.
year ;; variable to give turtle respective weight depending on what year of school they are in. the younger a turtle, the more susceptible as a perpetrator and victim.
year-weight ;; 1,2,3,4 correlating with the years of undergraduate for purpose as mentioned above
personality ;; implemented to give turtle university student like personality in terms of preferences and where to interact.
personality-var ;; allows the turtle to move intelligbly whilst being random due to the desire to fulfill a personal longing.
;;For example, if a turtle who likes to go to the fraternity a lot does not for a while, he will want to go and fulfill his desire. Enhances randomness and simulates student mindsets.
]

links-own [
 no-of-interactions-girl
 ;;implemented to track how many times female turtles interact with male turtles due to statistics iterating females have interacted with
 ;;their victim almsot 80% of the time. Again, implemented to mirror real like reference pattern. Create the interactions to be as accurate as possible.
]

to setup
  clear-all ;; clear all existing agents
  set bar patches with [pxcor < 0.5 and pycor > -1] ;; initializes patch-sets that are referred to throughout. Creating them like this makes it a lot easier to reference the enviornments.
  ask bar [set pcolor yellow + 2.5]                 ;; Cleans up the code from below.
  set frat patches with [pxcor > 0.5 and pycor > 0]
  ask frat [set pcolor black]
  set school patches with [pxcor <= 0.5 and pycor < 0]
  ask school [set pcolor white]
  set park patches with [pxcor > 0.5 and pycor < 0]
  ask park [set pcolor green + 2.5]
  set assault-place-count []


  ;ask patches
  ;[;;if pxcor <= 0.5 and pycor < 0 [set pcolor white] ;;old code that was orignally used to demarcate the world.
    ;if pxcor > 0.5 and pycor < 0 [set pcolor green + 2.5]
    ;if pxcor < 0.5 and pycor > -1 [set pcolor yellow + 2.5]]

  set-default-shape turtles "person" ;; defines the turtle shape that will be used. People to represent people.

  create-turtles men  [ ;; slider variable men that adjusts how many men turtles are made
    set sex 0 ;;sets their sex variable to 0 so that they can be distinguished from women.
    setxy random-xcor random-ycor ;;distributes the turtles throughout the world randomly
    set size 1 ;;visually pleasing.
    ]

  create-turtles women  [ ;; slider variable women that adjusts how many women are made
    set sex 1 ;;sets their sex variable to 1 so that they can be distinguished from men.
    setxy random-xcor random-ycor ;;distributes the turtles throughout the world randomly
    set size 1 ;;visually pleasing.
    ]

  ask turtles [
    set dict table:make ;;dictionary that is used to store and keep track of turtle who numbers and subsequent multiple interactons amongst male and female turtles.
    set personality one-of [1 2 3 4] ;;randomly assigns turtles to one of 4 personality types for intelligence and personality. Iterates real life desires and phenomeona.
    ifelse sex = 0 ;; used to color the agents appropiately depending on what year of studies they are in, Light pink to dark pink for females starting from freshman all the way to seniors.
        [set year one-of [1 2 3 4]] ;; light blue to dark blue for all male turtles indicating freshmen all the way to seniors.
        [set year one-of [5 6 7 8]]


      ]
  color-year ;;colors the turtles accordingly.
  vulnerability ;;sets year-weights to respective turtles. takes into account the statistic that younger people are more prone to be perpetrators or victims.
reset-ticks ;; resets counter
end 

to go ;; go function for interaction
  ;ask links [hide-link]
  ask turtles [
    move ;; moves turtles somewhat randomly whilst taking into account their personality.
   ; hostileinteraction] ;; intitial funciton that was used for turtle interaction
  interactfrat ;;interaction procedure unique to relatively statistical replicate prevailing traits and characteristics of sexual assault in a fraternity enviornment.
  interactbar ;;interaction procedure unique to relatively statistical replicate prevailing traits and characteristics of sexual assault in a bar like enviornment.
  interactpark ;;interaction procedure unique to relatively statistical replicate prevailing traits and characteristics of sexual assault in a park enviornment.
  interactschool ;;interaction procedure unique to relatively statistical replicate prevailing traits and characteristics of sexual assault in school enviornment.
  personality-need
  ];; variable that dictates a turtle moving to its personality niche depending on their threshold value.

  tick;;occurs per tick.
end 

to color-year ;; used this list to color the turtles based on their gender and years.
  ask turtles[
     if sex = 0 [
       if year = 1 [set color 108] ;; light blue (freshman male)
       if year = 2 [set color 107] ;; sophomore male
       if year = 3 [set color 106] ;; junior male
       if year = 4 [set color 105]];; dark blue (senior male)
     if sex = 1 [
       if year = 5 [set color 138] ;;light pink (freshman female)
       if year = 6 [set color 137] ;;sophomore female
       if year = 7 [set color 136] ;;junior female
       if year = 8 [set color 135]]];;dark pink (senior female)
end 

to personalityinitial ;;sets the original personality variable to 100. This fluctuates and dictates a turtles movement as turtles move away and from their niche.
  ask turtles [ set personality-var 100 ]
end 

to personality-need ;;creates 4 personality types depending on the 4 enviornment types in the world. Each personality has a preference to an enviornment.
  if personality = 1 [
    ifelse patch-here = one-of bar
      [set personality-var personality-var + 20]
      [set personality-var personality-var - .05]]
  if personality = 2 [
    ifelse patch-here = one-of frat
      [set personality-var personality-var + 20]
      [set personality-var personality-var - .05]]
  if personality = 3 [
    ifelse patch-here = one-of school
      [set personality-var personality-var + 20]
      [set personality-var personality-var - .05]]
  if personality = 4 [
    ifelse patch-here = one-of park
      [set personality-var personality-var + 20]
      [set personality-var personality-var - .05]]
end 

to vulnerability ;; playing with weight variables here for status in undergrad and possibility of being / perpotrating sexual assault.
  ask turtles[
      if sex = 0 [
       if year = 1 [set year-weight 4] ;; statistically based off of the fact that latter years decrease significantly in perpetrating or becoming a victim of assault (4 times less)
       if year = 2 [set year-weight 4]
       if year = 3 [set year-weight 1]
       if year = 4 [set year-weight .8]]
      if sex = 1 [
       if year = 5 [set year-weight 4]
       if year = 6 [set year-weight 4]
       if year = 7 [set year-weight 1]
       if year = 8 [set year-weight .8]]]
end 

to move ;; moves function for turtles. if the value is less than the defined threshold, the turtle will move towards its desired patch based on its personality type.
        ;; Allows for intelligence and personality types in agents and behavior.
    if personality = 1 [
      ifelse personality-var <= 0
       [face one-of bar
         fd 1]
         [rt random 90
           lt random 90
           fd 1]]
    if personality = 2 [
      ifelse personality-var <= 0
      [face one-of frat
        fd 1]
      [rt random 90
        lt random 90
        fd 1]]
    if personality = 3 [
      ifelse personality-var <= 0
      [face one-of school
         fd 1]
      [rt random 90
        lt random 90
        fd 1]]
    if personality = 4 [
      ifelse personality-var <= 0
      [face one-of park
         fd 1]
      [rt random 90
        lt random 90
        fd 1]]
end 

to assault
  set color red
  set assault-place-count fput pcolor assault-place-count
end 

to interactfrat ;; probability that sexual assault occurs based on relative weights derived from
                ;;statistically supported research that indicates prevailing sexual assault causes/characteristics in this enviornment as defined in paper.
    if pcolor = black [
      if sex = 0 [
        let target one-of turtles in-radius 3
          ifelse (table:has-key? dict ([who] of target)) [ ;; turtle checks in dictionary to see if the who number of the target within the radius is present, the number of target interactions is represented by the
            ;; notargetinteractions variable. it then takes the past interaction of the turtles and factors it into the probabililty of a female turtle being assaulted.
            let notargetinteractions (table:get dict ([who] of target))
            ask target [
              let awareness education?
              if (sex = 1 and random-float 10 < ((.4 * notargetinteractions) + (hostility * .4) + (alcohol * .8) - (empathy * .2) - (awareness * 2 * .45) + (year-weight)))
          [assault]]
            table:put dict [who] of target table:get dict [who] of target + 1]
          [table:put dict [who] of target 1
            ]]]
end 

to interactbar ;; probability that sexual assault occurs based on relative weights derived from
                ;;statistically supported research that indicates prevailing sexual assault causes/characteristics in this enviornment as defined in paper.
    if pcolor = yellow + 2.5 [
      if sex = 0 [
        let target one-of turtles in-radius 3
          ifelse (table:has-key? dict ([who] of target)) [ ;; turtle checks in dictionary to see if the who number of the target within the radius is present, the number of target interactions is represented by the
            ;; notargetinteractions variable. it then takes the past interaction of the turtles and factors it into the probabililty of a female turtle being assaulted.
            let notargetinteractions (table:get dict ([who] of target))
            ask target [
              let awareness education?
              if (sex = 1 and random-float 10 < ((.20 * notargetinteractions) + (hostility * .2) + (alcohol * .8) - (empathy * .2) - (awareness * 2 * .45) + (year-weight)))
          [assault]]
            table:put dict [who] of target table:get dict [who] of target + 1]
          [table:put dict [who] of target 1
            ]]]
end 

to interactpark ;; probability that sexual assault occurs based on relative weights derived from
                ;;statistically supported research that indicates prevailing sexual assault causes/characteristics in this enviornment as defined in paper.
    if pcolor = green + 2.5 [
      if sex = 0 [
        let target one-of turtles in-radius 3
          ifelse (table:has-key? dict ([who] of target)) [ ;; turtle checks in dictionary to see if the who number of the target within the radius is present, the number of target interactions is represented by the
            ;; notargetinteractions variable. it then takes the past interaction of the turtles and factors it into the probabililty of a female turtle being assaulted.
            let notargetinteractions (table:get dict ([who] of target))
            ask target [
              let awareness education?
              if (sex = 1 and random-float 10 < ((.15 * notargetinteractions) + (hostility * .1) + (alcohol * .2) - (empathy * .4) - (awareness * 2 * .45) + (year-weight)))
          [assault]]
            table:put dict [who] of target table:get dict [who] of target + 1]
          [table:put dict [who] of target 1
            ]]]
end 

to interactschool ;; probability that sexual assault occurs based on relative weights derived from
                ;;statistically supported research that indicates prevailing sexual assault causes/characteristics in this enviornment as defined in paper.
    if pcolor = white [
      if sex = 0 [
        let target one-of turtles in-radius 3
          ifelse (table:has-key? dict ([who] of target)) [ ;; turtle checks in dictionary to see if the who number of the target within the radius is present, the number of target interactions is represented by the
            ;; notargetinteractions variable. it then takes the past interaction of the turtles and factors it into the probabililty of a female turtle being assaulted.
            let notargetinteractions (table:get dict ([who] of target))
            ask target [
              let awareness education?
              if (sex = 1 and random-float 10 < ((.15 * notargetinteractions) + (hostility * .1) + (alcohol * 0) - (empathy * .4) - (awareness * 2 * .45) + (year-weight)))
          [assault]]
            table:put dict [who] of target table:get dict [who] of target + 1]
          [table:put dict [who] of target 1
            ]]]
end 







;;;;;;;;
;old functions that were used to compute probability without taking into account past interactions. Just so you can see the mental process I engaged in as I developed the model and
;shaped it to mirror real life phenomena.
;;;;;;;;

;to interactbar ;; probability that sexual assault occurs based on relative weights derived from
                ;;statistically supported research that indicates prevailing sexual assault causes/characteristics in this enviornment as defined in paper.
 ;   if pcolor = yellow + 2.5 [
  ;    if sex = 0 [
   ;     let target one-of turtles in-radius 3
    ;    ask target [ let awareness education?
     ;     if (sex = 1 and random-float 10 < ((hostility * .002) + (alcohol * .008) - (empathy * .002) - (awareness * 2 * .40) + (year-weight)))
      ;    [assault]]]]
;end


;to interactpark ;; probability that sexual assault occurs based on relative weights derived from
 ;               ;;statistically supported research that indicates prevailing sexual assault causes/characteristics in this enviornment as defined in paper.
  ;  if pcolor = green + 2.5 [
   ;   if sex = 0 [
    ;    let target one-of turtles in-radius 3
     ;   ask target [ let awareness education?
      ;    if (sex = 1 and random-float 10 < ((hostility * .001) + (alcohol * .002) - (empathy * .004) - (awareness * 2 * .40) + (year-weight)))
    ;      [assault]]]]
;end



;to interactschool ;; probability that sexual assault occurs based on relative weights derived from
 ;                 ;;statistically supported research that indicates prevailing sexual assault causes/characteristics in this enviornment as defined in paper.
  ;  if pcolor = white [
   ;   if sex = 0 [
    ;    let target one-of turtles in-radius 3
     ;   ask target [ let awareness education?
      ;    if (sex = 1 and random-float 10 < ((hostility * .001) + (alcohol * 0) - (empathy * .004) - (awareness * 2 * .40) + (year-weight)))
       ;   [assault]]]]
;end




;to hostileinteraction ;; probability that sexual assault is ar result in male hosility,alcohol intoxication, empathy, and awarness. ORIGINAL procedure that was developed and improved.
 ;if sex = 0 [
  ;let target one-of turtles in-radius 3
   ;ask target [ let awareness education?
    ;if (sex = 1 and random-float 10 < ((hostility * .001) + (alcohol * .008) - (empathy * .002) - (awareness * 2 * .30)))
     ;[set color red]]]
;end


;; This was the original function that I was working on implementing to track past turtle interaction and ultimately use to influence future interactions of other turtles given the
;; role of multiple prior interactions between female victims of sexual assault to males..

to go-and-count1
  ask turtles [
    if sex = 1 [
      fd 1
      if any? other turtles-here with [sex != 1] [
        ask one-of other turtles-here with [sex != 1] [
          ask link who [who] of myself [set no-of-interactions-girl no-of-interactions-girl + 1]]
          ]]]
end

There are 6 versions of this model.

Uploaded by	When	Description	Download
Christian Dayal	about 9 years ago	final version	Download this version
Christian Dayal	about 9 years ago	preliminary final.	Download this version
Christian Dayal	about 9 years ago	Updated interactions	Download this version
Christian Dayal	about 9 years ago	updated with graphical interfaces	Download this version
Christian Dayal	about 9 years ago	updated version with personalities and weights	Download this version
Christian Dayal	over 9 years ago	Initial upload	Download this version

Attached files

File	Type	Description	Last updated
May24.ChrisDayal.docx	word	Progress Report 3	over 9 years ago, by Christian Dayal	Download
Sexual Assault.png	preview	Preview for 'Sexual Assault'	over 9 years ago, by Christian Dayal	Download

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