Student Conscription Model

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;; STUDENT MILITARY SERVICE MOTIVATION MODEL
;; Based on research on motivations of students in Kyiv universities
;; to join military service after Russia's full-scale invasion of Ukraine
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;; GLOBAL VARIABLES
globals [
  war-week              ; Current week count since full-scale invasion
  media-influence       ; Level of positive media coverage of military (0-100)
  economic-hardship     ; Level of economic difficulty in the country (0-100)

  ;; Regional distribution percentages
  percent-west          ; Percentage of students from Western Ukraine
  percent-central       ; Percentage of students from Central Ukraine
  percent-east          ; Percentage of students from Eastern Ukraine
  percent-south         ; Percentage of students from Southern Ukraine

  ;; Event counters for tracking simulation events
  military-events       ; Count of significant military events
  economic-events       ; Count of significant economic events
  political-events      ; Count of significant political events
]

;; AGENT DEFINITIONS
breed [students student]

students-own [
  ;; Demographic attributes
  age                   ; Student age (17-26)
  gender                ; Student gender ("male" or "female")
  study-year            ; Year of study (1-4)
  region                ; Home region ("West", "Central", "East", "South")

  ;; Background factors (0-100 scale)
  family-influence      ; Level of patriotic/military influence from family
  educational-influence ; Level of patriotic/educational influence from school/university
  activism-involvement  ; Level of involvement in civic/political organizations

  ;; Motivation types (0-100 scale)
  social-motivation     ; Motivation from social environment and peers
  moral-motivation      ; Moral and psychological motivation
  political-motivation  ; Civic and political motivation
  economic-motivation   ; Economic/financial motivation

  ;; Decision variables
  motivation-threshold  ; Individual threshold required to join (varies by person)
  joined?               ; Whether student has joined military service

  ;; Network variables
  my-organization       ; Type of organization the student belongs to (if any)
  my-university         ; University the student attends
  peers                 ; List of connected peers
  my-peers-joined       ; Percentage of peers who have joined military
]

patches-own [
  university            ; University identifier (name)
  is-organization?      ; Whether patch represents an organization
  organization-type     ; Type of organization if applicable ("youth", "political", "volunteer")
]

;; MODEL SETUP PROCEDURES

to setup
  clear-all

  ;; Initialize regional distribution
  set percent-west 30    ; 30% of students from Western region
  set percent-central 40 ; 40% from Central region
  set percent-east 20    ; 20% from Eastern region
  set percent-south 10   ; 10% from Southern region

  set economic-hardship 80 ; Start with high economic hardship (wartime conditions)

  ;; Initialize event counters
  set military-events 0
  set economic-events 0
  set political-events 0

  ;; Set up the model environment and agents
  setup-environment
  setup-students
  setup-organizations
  reset-ticks
end 

;; Sets up the physical environment (universities and spaces)

to setup-environment
  ;; Initialize all patches to default state
  ask patches [
    set university "none"
    set is-organization? false
    set organization-type "none"
    set pcolor brown - 2  ; Default background color
  ]

  ;; Create university areas on the map
  setup-universities
end 

;; Creates student agents with appropriate attributes

to setup-students
  create-students population-size [
    set shape "person"
    set size 1  ; Set visible size for students

    ;; Initialize student attributes (demographics, motivations, etc.)
    setup-student-attributes

    ;; Place student at an appropriate university
    let target-university one-of patches with [university != "none"]

    ;; Fallback if no universities exist
    if target-university = nobody [
      move-to one-of patches
    ]

    ;; Place student at their assigned university
    if target-university != nobody [
      set my-university [university] of target-university

      ;; Try to find an unoccupied patch in the university
      let target-patch one-of patches with [(university = [my-university] of myself) and not any? students-here]

      ;; If all university patches are occupied, try nearby patches
      if target-patch = nobody [
        set target-patch one-of patches with [university = [my-university] of myself]

        ;; Last resort fallback
        if target-patch = nobody [
          set target-patch one-of patches
        ]
      ]

      ;; Move to the selected patch
      move-to target-patch

      ;; Add small random movement to avoid perfect alignment
      fd random-float 2
    ]
  ]
end 

;; Initialize individual student attributes based on research data

to setup-student-attributes
  ;; Set demographic attributes
  set age 17 + random 10  ; Ages 17-26 (typical university age range)
  set gender ifelse-value (random 100 < percent-female) ["female"] ["male"]
  set study-year 1 + random 4  ; Years 1-4 of university

  ;; Set regional background with appropriate probabilities
  let random-num random 100
  if random-num < percent-west [set region "West"]
  if random-num >= percent-west and random-num < (percent-west + percent-central) [set region "Central"]
  if random-num >= (percent-west + percent-central) and random-num < (percent-west + percent-central + percent-east) [set region "East"]
  if random-num >= (percent-west + percent-central + percent-east) [set region "South"]

  ;; Initialize influence factors based partly on region
  set family-influence setup-family-influence
  set educational-influence setup-educational-influence
  set activism-involvement 0 ; Will be updated when organizations form

  ;; Initialize motivation factors with gender differences based on research
  ifelse gender = "female" [
    ;; Female students - research shows higher moral components
    set social-motivation random 30 + 5
    set moral-motivation random 30 + 10
    set political-motivation random 30
    set economic-motivation random 30 - 5
  ] [
    ;; Male students
    set social-motivation random 30
    set moral-motivation random 30
    set political-motivation random 30 + 5
    set economic-motivation random 30
  ]

  ;; Set individual threshold (varies by person and gender)
  ifelse gender = "female" [
    ;; Women typically require higher motivation due to gender barriers in military
    set motivation-threshold 60 + random 40
  ] [
    ;; Men's threshold
    set motivation-threshold 50 + random 50
  ]

  ;; Initialize decision and network variables
  set joined? false
  set peers []
end 

;; Calculate family influence based on regional background

to-report setup-family-influence
  let base-influence random 60

  ;; Regional effects on family influence based on research
  if region = "West" [set base-influence base-influence + 20]  ; Western regions more patriotic
  if region = "South" or region = "East" [set base-influence max list 0 (base-influence - 10)]  ; Less patriotic influence

  report min list 100 base-influence  ; Cap at 100
end 

;; Calculate educational influence based on university quality and region

to-report setup-educational-influence
  let base-influence random 50
  let uni my-university

  ;; Higher quality education in prestigious universities
  if uni = "NaUKMA" [set base-influence base-influence + 20]  ; Kyiv-Mohyla Academy
  if uni = "KNU" [set base-influence base-influence + 15]     ; Kyiv National University
  if uni = "LNU" [set base-influence base-influence + 10]     ; Lviv National University

  ;; Regional effects on educational influence
  if region = "West" [set base-influence base-influence + 5]  ; Western universities more nationally oriented

  report min list 100 base-influence  ; Cap at 100
end 

;; Create organizations (youth, political, volunteer) on the map

to setup-organizations
  ;; Number of each organization type
  let num-youth-orgs 3 + random 2      ; 3-4 youth organizations
  let num-political-orgs 2 + random 3  ; 2-4 political organizations
  let num-volunteer-orgs 4 + random 3  ; 4-6 volunteer organizations

  ;; Create youth organizations
  ask n-of num-youth-orgs patches with [not is-organization? and university != "none"] [
    set is-organization? true
    set organization-type "youth"
    set pcolor yellow
  ]

  ;; Create political organizations
  ask n-of num-political-orgs patches with [not is-organization? and university != "none"] [
    set is-organization? true
    set organization-type "political"
    set pcolor blue
  ]

  ;; Create volunteer organizations
  ask n-of num-volunteer-orgs patches with [not is-organization? and university != "none"] [
    set is-organization? true
    set organization-type "volunteer"
    set pcolor green
  ]

  ;; Students join organizations based on their attributes and proximity
  ask students [
    ;; Find nearby organizations (within radius of 5 patches)
    let nearby-orgs patches in-radius 5 with [is-organization?]

    ;; If there are nearby organizations, possibly join one based on student characteristics
    if any? nearby-orgs [
      let chosen-org one-of nearby-orgs
      let join-probability 0

      ;; Calculate join probability based on organization type and student characteristics
      if [organization-type] of chosen-org = "youth" [
        ;; Younger students more likely to join youth orgs
        set join-probability 70 - ((age - 17) * 10)
      ]

      if [organization-type] of chosen-org = "political" [
        ;; Political orgs appeal to students with political motivation
        set join-probability political-motivation / 2
      ]

      if [organization-type] of chosen-org = "volunteer" [
        ;; Volunteer orgs appeal more to students with moral motivation
        set join-probability moral-motivation / 2
      ]

      ;; Regional effects on organization joining
      if region = "West" and [organization-type] of chosen-org = "volunteer" [
        set join-probability join-probability + 20  ; Western regions more volunteer-oriented
      ]

      if region = "East" and [organization-type] of chosen-org = "political" [
        set join-probability join-probability + 15  ; Eastern regions more politically active
      ]

      ;; Join organization if probability threshold met
      if random 100 < join-probability [
        set my-organization [organization-type] of chosen-org

        ;; Being in an organization increases activism involvement
        set activism-involvement 20 + random 40

        ;; Different organization types affect different motivations
        if my-organization = "youth" [
          set social-motivation social-motivation + 10
        ]
        if my-organization = "political" [
          set political-motivation political-motivation + 15
        ]
        if my-organization = "volunteer" [
          set moral-motivation moral-motivation + 15
        ]
      ]
    ]
  ]
end 

;; Create university areas on the map based on real geography

to setup-universities
  ;; Define number of universities
  let num-universities 6  ; All 6 universities to match research data

  ;; List of university names
  let university-names ["NaUKMA" "KNU" "LNU" "KhNU" "ONPU" "ChNU"]

  ;; Regions associated with each university
  let university-regions ["Central" "Central" "West" "East" "South" "Central"]

  ;; University quality factors (0-100) - affects educational influence
  let university-quality [85 75 70 65 60 65]

  ;; Coordinates for each university based on approximate real geography
  let university-coordinates [
    [0 0]     ; NaUKMA - Kyiv (Central)
    [5 -2]    ; KNU - Kyiv (Central)
    [-15 5]   ; LNU - Lviv (West)
    [18 -5]   ; KhNU - Kharkiv (East)
    [5 -15]   ; ONPU - Odesa (South)
    [-5 -10]  ; ChNU - Chernivtsi (Central-West)
  ]

  ;; University size (radius) to create appropriate areas
  let university-sizes [3 6 6 6 6 5]

  ;; Create each university in its geographic location
  let university-counter 0

  repeat num-universities [
    ;; Skip if we've run out of university names
    if university-counter >= length university-names [stop]

    ;; Get the current university coordinates and radius
    let center-x item 0 (item university-counter university-coordinates)
    let center-y item 1 (item university-counter university-coordinates)
    let radius item university-counter university-sizes

    ;; Get the current university name and associated data
    let current-name item university-counter university-names
    let current-region item university-counter university-regions
    let current-quality item university-counter university-quality

    ;; Create a cluster of patches for this university
    ask patches with [(pxcor - center-x) ^ 2 + (pycor - center-y) ^ 2 < radius ^ 2] [
      set university current-name

      ;; Set colors based on university quality (unique shade for each university)
      set pcolor scale-color blue current-quality 0 100
      set plabel-color white

      ;; Occasionally label a patch with university name for visualization
      if random 100 < 10 and (pxcor - center-x) ^ 2 + (pycor - center-y) ^ 2 < (radius - 1) ^ 2 [
        set plabel current-name
      ]
    ]

    ;; Increment counter
    set university-counter university-counter + 1
  ]
end 

;; MAIN SIMULATION PROCEDURES

to go
  if ticks >= simulation-length [stop]  ; End simulation after specified time

  ;; Advance war timeline
  set war-week ticks

  ;; Update environmental conditions (media, economy, events)
  update-environment

  ;; Students interact and update motivations
  ask students [
    interact-with-peers
    update-motivations
    decide-to-join
  ]

  ;; Update visualization
  update-display

  tick
end 

;; Update environmental conditions affecting all students

to update-environment
  ;; Initialize media influence on first tick
  if ticks = 0 [
    set media-influence 50  ; Start at neutral value
  ]

  ;; Update media influence based on slider and random fluctuations
  set media-influence (media-coverage + random-float 5 - 2.5)
  set media-influence max list 0 min list 100 media-influence  ; Keep within 0-100 range

  ;; Economy gradually fluctuates with war duration
  set economic-hardship max list 0 (economic-hardship + random-float 2 - 1)

  ;; Apply environmental effects to students based on their characteristics
  ask students [
    ;; Recruitment campaigns affect social motivation
    set social-motivation social-motivation +
      (recuitment-campaign-intensity / 100) * social-weight

    ;; Recruitment campaigns also affect economic motivation but less strongly
    set economic-motivation economic-motivation +
      (recuitment-campaign-intensity / 200) * economic-weight

    ;; Eastern and Southern regions face more economic impact during war
    if region = "East" or region = "South" [
      set economic-motivation economic-motivation + (economic-hardship / 200)
    ]

    ;; Media influence affects political motivation differently based on education level
    set political-motivation political-motivation +
      (media-influence / 100) * (educational-influence / 100) * political-weight
  ]

  ;; Occasional major events that affect motivations (roughly every 10 weeks)
  if war-week mod 10 = 0 and war-week > 0 [
    let event-type random 3

    ;; Major military event (increases moral motivation)
    if event-type = 0 [
      set military-events military-events + 1
      ask students [
        set moral-motivation moral-motivation + random-float 10
      ]
    ]

    ;; Economic support package (increases economic motivation)
    if event-type = 1 [
      set economic-events economic-events + 1
      ask students [
        set economic-motivation economic-motivation + random-float 15
      ]
    ]

    ;; Political development (increases political motivation)
    if event-type = 2 [
      set political-events political-events + 1
      ask students [
        set political-motivation political-motivation + random-float 12
      ]
    ]
  ]
end 

;; Students interact with peers and update their social network

to interact-with-peers
  ;; Find nearby peers within interaction radius
  let nearby-peers other students in-radius interaction-radius

  ;; Store nearby peers list
  set peers nearby-peers

  ;; Calculate the percentage of peers who have joined military
  ifelse any? nearby-peers [
    set my-peers-joined (count nearby-peers with [joined?] / count nearby-peers) * 100
  ] [
    set my-peers-joined 0  ; No peers, so set to 0
  ]
end 

;; Update student motivation levels based on various factors

to update-motivations
  ;; Calculate peer influence
  let joined-peers 0
  let total-peers count peers

  if total-peers > 0 [
    set joined-peers count peers with [joined?]
  ]

  ;; Social motivation increases when peers join
  set social-motivation social-motivation +
    (joined-peers / max list 1 total-peers) * social-weight

  ;; Moral motivation increases with war duration
  set moral-motivation moral-motivation +
    (war-week / 50) * moral-weight

  ;; Political motivation affected by activism involvement
  set political-motivation political-motivation +
    (activism-involvement / 100) * political-weight

  ;; Economic motivation affected by economic conditions
  set economic-motivation economic-motivation +
    (economic-hardship / 100) * economic-weight

  ;; Gender-specific motivation updates based on research
  if gender = "female" [
    ;; Research shows women have higher responsibility for state welfare
    set moral-motivation moral-motivation +
      (war-week / 40) * moral-weight

    ;; Women more motivated to prove themselves against stereotypes
    set social-motivation social-motivation +
      (war-week / 200) * social-weight
  ]

  ;; Apply natural decay to motivations over time (prevents unlimited growth)
  set social-motivation min list 100 (social-motivation * 0.97)
  set moral-motivation min list 100 (moral-motivation * 0.99)
  set political-motivation min list 100 (political-motivation * 0.98)
  set economic-motivation min list 100 (economic-motivation * 0.96)
end 

;; Make decision about joining military based on motivations and barriers

to decide-to-join
  if joined? [stop]  ; Skip if already joined

  ;; Calculate overall motivation (weighted sum of motivation types)
  let overall-motivation (
    (social-motivation * social-weight) +
    (moral-motivation * moral-weight) +
    (political-motivation * political-weight) +
    (economic-motivation * economic-weight)
  ) / (social-weight + moral-weight + political-weight + economic-weight)

  ;; Apply barriers based on research findings
  if contract-duration = "3-years" [
    ;; Longer contracts reduce likelihood (significant barrier identified in research)
    set overall-motivation overall-motivation * 0.8
  ]

  if study-service-compatibility < 50 [
    ;; Lower compatibility between studies and service is a barrier
    set overall-motivation overall-motivation * (0.5 + (study-service-compatibility / 100))
  ]

  ;; Make decision to join if motivation exceeds threshold
  if overall-motivation > motivation-threshold [
    set joined? true
    set color red
  ]
end 

;; Update display elements for visualization

to update-display
  ;; Update student colors based on joined status
  ask students [
    ifelse joined?
      [ set color red ]     ; Joined military (red)
      [ set color green ]   ; Not joined (green)
  ]
end