# Aspiration, Attainment and Success (JASSS 2013)

Model was written in NetLogo 5.0
•
Viewed 780 times
•
Downloaded 47 times
•
Run 0 times

Do you have questions or comments about this model? Ask them here! (You'll first need to log in.)

## Comments and Questions

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

Click to Run Model

;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;; ;; ;; School Choice November 2012 ;; ;; ;; ;; Code licenced by James D.A. Millington (http://www.landscapemodelling.net) ;; ;; under a Creative Commons Attribution-Noncommercial-Share Alike 3.0 ;; ;; Unported License (see http://creativecommons.org/licenses/by-nc-sa/3.0/) ;; ;; ;; ;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;;; ;Full documentation at ... extensions [ shell r ] globals [ schoolRadii empty-rankings directory exp-index ;experiment number (for files/directories) ;Moran's i summary asp-moran-i ;Aspiration Moran's i asp-moran-i-p ;Aspiration Moran's i p-value att-moran-i ;Attainment Moran's i att-moran-i-p ;Attainment Moran's i p-value ;relationships summary GA-m ;GCSE vs AppRatio coefficient GA-r ;GCSE vs AppRatio Pearson r GA-p ;GCSE vs AppRatio p value GMx-m ;GCSE vs Max Distance coefficient GMx-r ;GCSE vs Max Pearson r GMx-p ;GCSE vs Max p value GMn-m ;GCSE vs Mean Distance coefficient GMn-r ;GCSE vs Mean Pearson r GMn-p ;GCSE vs Mean p value AMx-m ;AppRatio vs Max Distance coefficient AMx-r ;AppRatio vs Max Distance Pearson r AMx-p ;AppRatio vs Max Distance p value AMn-m ;AppRatio vs Mean Distance coefficient AMn-r ;AppRatio vs Mean Distance Pearson r AMn-p ;AppRatio vs Mean Distance p value ] breed [parents parent] breed [schools school] parents-own [ strategy ;indicator of which ranking method agent used rankings ;list of schools that are worthy of ranking (transfered into specific ranks rank1, rank2... etc) distances ;list of schools in ascending of order of distance allocated-school ;school allocated allocated-distance ;distance to allocated school aspiration ;aspiration level of parent success-by-rank ;rank of allocated school (1 is top rank, i.e. most preferred) success-rank1 ;true if allocated to top-ranked school, else false (or -1 if not allocated) success-by-aspiration ;true if allocated school GCSE-score > aspiration at time of allocation considered ; list of schools considered acceptable given aspiration catchment ; list of schools the parent believes they are in the catchment of (given last 3 years catchments) - 3? or memory? avoided ; list of schools the parent wishes to avoid because school GCSE-score is some level below their aspiration child-age ;age of child. children apply for school when 10 years old (therefore only rank and allocate when child = 10) child-attainment ; initially set to parent aspiration, can increase during school years want-to-move ;true or false - does this parent want to move? have-moved ; true or false - has this parent moved? if so cannot move again move-target ;if parent wants to move, this is the preferred school initialHome ;patch where Parent initially lives newHome ;patch where Parent moves to ] schools-own [ school-type ;state or new? id ;school id GCSE-score ;measure of school quality ;GCSE-z-score ;z-score of school GCSE score GCSE-scores ; list containing last MEMORY years GCSE-scores value-added; % by which incoming students aspiration is increased year-on-year to y11 mean-aspiration mean-attainment ;added v6 places ;pupil places available at the school for each year last-growth ;last tick in which school expanded y7pupils ;number of pupils allocated this year all-pupils ;total number of pupils in the school allocated ;list holding allocated parents all-applicants ;list holding all applicants for this year with given criteria (see below) applicants ;list holding applicants for this year - changes through application process (allocate-places) app-ratio ;ratio of applications to places max-distance ;distance of farthest allocated parent max-distances ;list of last Parent-Memory years' max distances mean-distance ; mean distance of parents mean-distances ;list of last Parent-Memory years' mean distances y7Parents ;list of parents with children in year 7 (initially this is simply a value specifying that year's GCSE score, through time becomes a list which is updated each year) y8Parents ;list of parents with children in year 8 (initially this is simply a value specifying that year's GCSE score, through time becomes a list which is updated each year) y9Parents ;list of parents with children in year 9 (initially this is simply a value specifying that year's GCSE score, through time becomes a list which is updated each year) y10Parents ;list of parents with children in year 10 (initially this is simply a value specifying that year's GCSE score, through time becomes a list which is updated each year) y11Parents ;list of parents with children in year 11 (initially this is simply a value specifying that year's GCSE score, through time becomes a list which is updated each year) catchmentPatches ; patches within school's max-distance with no parents in them ] patches-own [ location-value ;value of location for moving p-aspiration ;aspiration of parent on this patch (for calculating Moran's I) p-attainment ;child-attainment of parent on this patch (for calculating Moran's I) ] ;;---------------------------------- ;;SETUP ;;---------------------------------- to setup clear-all if(calc-Moran?) [ setup-R ] random-seed seed setup-empty-rankings set schoolRadii sqrt((SchoolSize * 5) / pi) ;specifies the radius of a circle with area equal to the number of places at a school (i.e. 5 years of pupils) if(Random-Schools = false) [ set Families 100 ;slider - describes number of parents per school to add at each tick set SchoolSize 100 ;slider - initial size of a single year group at school set Number-of-Schools 9 ;slider - initial number of schools ] setup-Parents setup-Schools setup-Patches reset-ticks plotting end to setup-Patches print "setting up patches" set-patch-attributes end to setup-empty-rankings set empty-rankings[] let thisRank length empty-rankings while[thisRank < Number-of-Ranks] [ set empty-rankings lput -1 empty-rankings set thisRank thisRank + 1 ] end to setup-Schools print "setting up schools" ;if schools are randomly positioned in space ifelse(Random-Schools) [ while[count schools < Number-of-Schools] [ ask one-of patches [ ;minimum spacing requirement if(not any? other schools with [distance myself < world-width * Min-School-Spacing ]) [ set plabel 1 set plabel-color black ;move any parents already at this location - schools and parents cannot share a location ask parents-here [ let unoccupiedPatch one-of patches with [not any? turtles-here] move-to unoccupiedPatch ] ;create the school sprout-schools 1 [ set size 3 set shape "house" set school-type "state" set GCSE-score -1 while [GCSE-score < 0 or GCSE-score > 100] [ if(Initial-School-GCSE-Distribution = "uniform") [ set GCSE-score 1 ] if(Initial-School-GCSE-Distribution = "normal") [ set GCSE-score random-normal 50 20 ] if(Initial-School-GCSE-Distribution = "negative-exponential") [ set GCSE-score random-exponential 25 ] ] set GCSE-scores [] set value-added -2 if(School-Value-Added) [ while [value-added < -1 or value-added > 1 ] [ if(School-Value-Added-Distribution = "uniform") [ set value-added 0.1 ] if(School-Value-Added-Distribution = "normal") [ set value-added random-normal 0 0.1 ] if(value-added < 0) [ set value-added (value-added * -1) ] ;do not allow value-added to be negative ;to check influence of increased value-added ;set value-added value-added + 0.1 ] ] ;lists that will hold parents in each year group (initially empty) set y7Parents [] set y8Parents [] set y9Parents [] set y10Parents [] set y11Parents [] set places SchoolSize set last-growth 0 set id (count schools - 1) ;first school has id of zero set color (count schools - 1) * 10 + 15 ;first school will be red ;set size 0 set max-distances [] set mean-distances [] set allocated [] set applicants [] set mean-distance 0 ] ] ] ] ] ;else schools are on a grid [ while[count schools < 9] [ let school-xcor 0 let school-ycor 0 let third-x (world-width / 3) let third-y (world-height / 3) if(count schools = 6) [ set school-xcor floor(third-x * -1) set school-ycor floor(third-y * -1) ] if(count schools = 7) [ set school-xcor 0 set school-ycor floor(third-y * -1) ] if(count schools = 8) [ set school-xcor floor(third-x) set school-ycor floor(third-y * -1) ] if(count schools = 3) [ set school-xcor floor(third-x * -1) set school-ycor 0 ] if(count schools = 5) [ set school-xcor floor(third-x) set school-ycor 0 ] if(count schools = 0) [ set school-xcor floor(third-x * -1) set school-ycor floor(third-y) ] if(count schools = 1) [ set school-xcor 0 set school-ycor floor(third-y) ] if(count schools = 2) [ set school-xcor floor(third-x) set school-ycor floor(third-y) ] ask patches with [pxcor = school-xcor and pycor = school-ycor] [ if(not any? other schools with [distance myself < world-width * Min-School-Spacing ]) [ set plabel 1 set plabel-color black ask parents-here [ let unoccupiedPatch one-of patches with [not any? turtles-here] move-to unoccupiedPatch ] sprout-schools 1 [ set size 3 set shape "house" set school-type "state" set GCSE-score -1 while [GCSE-score < 0 or GCSE-score > 100] [ if(Initial-School-GCSE-Distribution = "uniform") [ set GCSE-score 1 ] if(Initial-School-GCSE-Distribution = "normal") [ set GCSE-score random-normal 50 20 ] if(Initial-School-GCSE-Distribution = "negative-exponential") [ set GCSE-score random-exponential 25 ] ] set GCSE-scores [] set value-added -2 if(School-Value-Added) [ while [value-added < -1 or value-added > 1 ] [ if(School-Value-Added-Distribution = "uniform") [ set value-added 0.1 ] if(School-Value-Added-Distribution = "normal") [ set value-added random-normal 0 0.1 ] if(value-added < 0) [ set value-added (value-added * -1) ] ;do not allow value-added to be negative ;to check influence of increased value-added ;set value-added value-added + 0.1 ] ] set y7Parents [] set y8Parents [] set y9Parents [] set y10Parents [] set y11Parents [] set places SchoolSize set id (count schools - 1) ;first school has id of zero set color (count schools - 1) * 10 + 15 ;first school will be red ;set size 0 set max-distances [] set mean-distances [] set allocated [] set applicants [] set mean-distance 0 ] ] ] ] ] end to setup-Parents print "setting up parents" ;initially set 7 x Families * Number-of-Schools with evenly distributed child ages (9-15) let addedParents 0 while [addedParents < (Families * Number-of-Schools * 7)] [ ask one-of patches [ if(not any? turtles-here) [ sprout-parents 1 [ set color grey set size 1 facexy 0 0 set shape "circle" set aspiration -1 while [aspiration < 0 or aspiration > 100] [ if(Parent-Aspiration-Distribution = "uniform") [ set aspiration random (Aspiration-Mean * 2) ] if(Parent-Aspiration-Distribution = "normal") [ set aspiration random-normal Aspiration-Mean 20 ] if(Parent-Aspiration-Distribution = "negative-exponential") [ set aspiration random-exponential 25 ] if(Parent-Aspiration-Distribution = "exponential") [ set aspiration random-exponential 25 ] ] if(Parent-Aspiration-Distribution = "exponential") [ set aspiration 100 - aspiration ] ifelse(attainment=aspiration?) [ set child-attainment aspiration ] [ set child-attainment -1 while [child-attainment < 0 or child-attainment > 100] [ if(Child-Attainment-Distribution = "uniform") [ set child-attainment random (Attainment-Mean * 2) ] if(Child-Attainment-Distribution = "normal") [ set child-attainment random-normal Attainment-Mean 20 ] if(Child-Attainment-Distribution = "negative-exponential") [ set child-attainment random-exponential 25 ] if(Child-Attainment-Distribution = "exponential") [ set child-attainment random-exponential 25 ] ] if(Child-Attainment-Distribution = "exponential") [ set child-attainment 100 - child-attainment ] ] set child-age (floor ((addedParents + 1) / (Families * Number-of-Schools))) + 9 set allocated-school 0 set have-moved false set want-to-move true set initialHome myself set newHome nobody set rankings [] set success-by-rank -1 set success-rank1 -1 set success-by-aspiration -1 set strategy -1 ] set addedParents addedParents + 1 ] ] ] ;there always seems to be one parent with child-age = 16 which 'should' be 9. this fixes that if(any? parents with [child-age = 16]) [ ask parents with [child-age = 16] [ set child-age 9 ] ] end to set-parent-school-distance set distances sort-by [distance ?1 < distance ?2] schools end ;;---------------------------------- ;;END SETUP ;;---------------------------------- ;;---------------------------------- ;;SIMULATION ;;---------------------------------- to go if(ticks = 0) [ with-local-randomness [ if(Export-Summary-Data or Export-World-Data or Export-Movie) [ ;create a new directory for this model run set directory "J:\\SchoolChoice" ;set directory "C:\\Users\\James\\Dropbox\\Research\\OngoingProjects\\SchoolChoice" set-current-directory directory shell:cd directory print directory print shell:pwd ;create a dummy file to check what new name to give the directory (checked in next-index procedure) let dummy "Experiment" let suffix ".txt" set exp-index next-index dummy suffix let filename (word shell:pwd "\\" dummy exp-index suffix) file-open filename write-experiment-data file-close ;set the new directory name and create set directory (word shell:pwd "\\" dummy exp-index) ;set show(shell:exec "cmd" "/c" "md" directory) ;create set-current-directory directory ;update shell:cd directory ;update ] if(Export-Summary-Data) [ ExportSummaryData_header ] if(Export-World-Data) [ ExportWorldData_initial ] if(Export-Movie) [ movie-start "movie.mov" movie-set-frame-rate 2 movie-grab-view ] ] ask parents [set-parent-school-distance] set-SchoolCatchments rank-Schools move ] show "Adding new parents and aging children" age-children age-PupilCohorts ;move cohorts of students up one year add-NewParents ;add new parents for this tick set-schoolCatchments ;find patches in catchment available to move into this tick (do this after adding new parents) show "Parents ranking schools" rank-Schools ;parents set their school ranking show "Allocating places" allocate-Places ;schools allocate places to parents with child-age = 10 show "Moving agents" move ;parents with child-age = 9 potentially move to a better location set-patch-attributes show "Updating Schools" calc-catchment-size ;schools calculate mean and max allocated distance of their parents update-SchoolGCSE ;update schools' GCSE-score with-local-randomness [ show "Plotting etc" check-success update-colours plotting if(Export-Summary-Data) [ calc-Moran calc-relationships ExportSummaryData ] if(Export-World-Data) [ ExportWorldData ] if(Export-Movie) [ movie-grab-view ] ] tick if(ticks = run-length) [ if(Export-Movie) [ movie-close ] if(Export-Summary-Data) [ export-worldview ZipParents_Data ] stop ] end to distribute-parents-worst-best [ worst best ] ;distributes parents currently at worst (school) to best ask worst [ ask best [ set y7Parents sentence y7Parents [y7Parents] of myself ] ask best[ set y8Parents sentence y8Parents [y8Parents] of myself ] ask best[ set y9Parents sentence y9Parents [y9Parents] of myself ] ask best[ set y10Parents sentence y10Parents [y10Parents] of myself ] ask best[ set y11Parents sentence y11Parents [y11Parents] of myself ] ask best[ set allocated sentence allocated [allocated] of myself ] ] ask parents with [allocated-school = worst] [ set allocated-school best ] ask best[ set places length allocated ] ask worst [ die ] ask parents [ set-parent-school-distance ] update-Colours end to distribute-parents-equally [ worst ] ;distributes parents currently at worst (school) equally among other schools ask worst [ ;show "moving y7Parents" set y7Parents shuffle y7Parents while[length y7Parents > 0] [ ask one-of other schools [ set y7Parents sentence y7Parents first [y7Parents] of myself ] set y7Parents remove-item 0 y7Parents ] ;show "moving y8Parents" set y8Parents shuffle y8Parents while[length y8Parents > 0] [ ask one-of other schools [ set y8Parents sentence y8Parents first [y8Parents] of myself ] set y8Parents remove-item 0 y8Parents ] ;show "moving y9Parents" set y9Parents shuffle y9Parents while[length y9Parents > 0] [ ask one-of other schools [ set y9Parents sentence y9Parents first [y9Parents] of myself ] set y9Parents remove-item 0 y9Parents ] ;show "moving y10Parents" set y10Parents shuffle y10Parents while[length y10Parents > 0] [ ask one-of other schools [ set y10Parents sentence y10Parents first [y10Parents] of myself ] set y10Parents remove-item 0 y10Parents ] ;show "moving y11Parents" set y11Parents shuffle y11Parents while[length y11Parents > 0] [ ask one-of other schools [ set y11Parents sentence y11Parents first [y11Parents] of myself ] set y11Parents remove-item 0 y11Parents ] ;show "moving allocated" set allocated shuffle allocated while[length allocated > 0] [ ask one-of other schools [ set allocated sentence allocated first [allocated] of myself ] set allocated remove-item 0 allocated ] ] ask worst [ die ] ask schools [ foreach y7Parents [ ask ? [ if(allocated-school != myself) [ set allocated-school myself ] ] ] foreach y8Parents [ ask ? [ if(allocated-school != myself) [ set allocated-school myself ] ] ] foreach y9Parents [ ask ? [ if(allocated-school != myself) [ set allocated-school myself ] ] ] foreach y10Parents [ ask ? [ if(allocated-school != myself) [ set allocated-school myself ] ] ] foreach y11Parents [ ask ? [ if(allocated-school != myself) [ set allocated-school myself ] ] ] foreach allocated [ ask ? [ if(allocated-school != myself) [ set allocated-school myself ] ] ] ] ask schools [ if(places < length allocated) [set places length allocated ] ;don't decreease places, only increase if necessary ] ask parents [ set-parent-school-distance ] update-Colours end to-report remove-first-n-list-items [ thisList n ] if(length thisList > 0) [ let removed 0 while[removed < n and length thisList > 0] [ set thisList remove-item 0 thisList set removed removed + 1 ] ] report thisList end to add-NewParents let addedParents 0 while [addedParents < Families * Number-of-Schools] [ let sprouting-patch nobody ifelse(Location-Rules = false) ;if new parents can be located randomly on the grid [ ask one-of patches [ if(not any? turtles-here) [ create-parent set addedParents addedParents + 1 ] ] ] ;otherwise only allow parents to move to patches with location-value lower than their aspiration [ ask patch 0 0 [ create-parent ] ask parents-on patch 0 0 [ let newPatch patch-here let myAspiration aspiration set newPatch max-one-of patches with [not any? turtles-here and location-value < myAspiration ] [location-value] if(newPatch = nobody) [set newPatch min-one-of patches with [not any? turtles-here ] [location-value]] ;if there are no patches with patchVAlue < aspiration, move to patch available with minimum location-value move-to newPatch set initialHome newPatch ] set addedParents addedParents + 1 ] ] end to create-parent sprout-parents 1 [ set color grey if(Show-Unallocated = false) [ set hidden? true ] set size 1 facexy 0 0 set shape "circle" set aspiration -1 while [aspiration < 0 or aspiration > 100] [ if(Parent-Aspiration-Distribution = "uniform") [ set aspiration random (Aspiration-Mean * 2) ] if(Parent-Aspiration-Distribution = "normal") [ set aspiration random-normal Aspiration-Mean 20 ] if(Parent-Aspiration-Distribution = "negative-exponential") [ set aspiration random-exponential 25 ] if(Parent-Aspiration-Distribution = "exponential") [ set aspiration random-exponential 25 ] ] if(Parent-Aspiration-Distribution = "exponential") [ set aspiration 100 - aspiration ] ifelse(attainment=aspiration?) [ set child-attainment aspiration ] [ set child-attainment -1 while [child-attainment < 0 or child-attainment > 100] [ if(Child-Attainment-Distribution = "uniform") [ set child-attainment random (Attainment-Mean * 2) ] if(Child-Attainment-Distribution = "normal") [ set child-attainment random-normal Attainment-Mean 20 ] if(Child-Attainment-Distribution = "negative-exponential") [ set child-attainment random-exponential 25 ] if(Child-Attainment-Distribution = "exponential") [ set child-attainment random-exponential 25 ] ] if(Child-Attainment-Distribution = "exponential") [ set child-attainment 100 - child-attainment ] ] set child-age 9 set have-moved false set want-to-move true set initialHome myself set newHome nobody set allocated-school 0 set rankings [] set-parent-school-distance set success-by-rank -1 set success-rank1 -1 set success-by-aspiration -1 set strategy -1 ] end to age-children ask parents [ set child-age child-age + 1 ] ;kill parents with children that have left school ask parents with [child-age = 16] [die ] end to age-PupilCohorts ;move each cohort of students up one year (by replacing parent lists with previous year's parent list) ;create y7Parents from the allocated list for the school ;don't age cohorts in the first tick because there no pupils have been allocated yet if(ticks > 0) [ ask schools [ set y11Parents [] foreach y10Parents [ set y11Parents fput ? y11Parents] set y10Parents [] foreach y9Parents [ set y10Parents fput ? y10Parents] set y9Parents [] foreach y8Parents [ set y9Parents fput ? y9Parents] set y8Parents [] foreach y7Parents [ set y8Parents fput ? y8Parents] set y7Parents [] foreach allocated [set y7Parents fput ? y7Parents ] ;copy allocated to y7Parents (allocated are parents with child-age = 10 last year, now child-age = 11) ] ] end to allocate-Places ask schools [ set all-applicants [] set all-applicants parents with [child-age = 10 and member? myself rankings and allocated-school = 0] set app-ratio (count all-applicants) / places set y7pupils 0 ;re-set number of year 7 pupils for this year of allocations set allocated [] ] ;all schools allocate applicants that ranked them highest first (potentially using distance if there are too many applicants) ;then school allocate applicants that ranked them second (again, potentially using distance if there are too many applicants), third, fourth, etc. ;schools that have remaining places after all ranked preferences have been allocated, allocate remaining places on distance or randomly let thisRank 0 while[thisRank < Number-of-Ranks] [ ask schools [ if(y7pupils < places) [ set applicants parents with [child-age = 10 and item thisRank rankings = myself and allocated-school = 0] ;add parents to applicants list if they have ranked this school highest if(school-type = "state") [ set applicants sort-by [distance ?1 < distance ?2] applicants ;sort the list of applicants, closest is first in list NOTE: this sorting changes agentset to a list ] if(school-type = "new") [ set applicants sort-by [[child-attainment] of ?1 > [child-attainment] of ?2] applicants ] ;sort the list of applicants, highest attainment is first in list NOTE: this sorting changes agentset to a list ifelse(length applicants > (places - y7pupils)) ;if there are more applicants than places available at the school, allocate by distance [ while [y7pupils < places] ;while not all places have been allocated [ ask first applicants [ set allocated-school myself ] ;allocate the closest applicant ;ask first applicants [ set allocated-school myself set rankings empty-rankings ] ;allocate the current 'best' applicant set allocated lput first applicants allocated ;add this current 'best' applicant to the allocated list set applicants remove-item 0 applicants ;remove this current 'best' applicant from the applicants list set y7pupils y7pupils + 1 ;increase number of places allocated by 1 ] ] ;if there are more places than applicants allocate all applicants a place [ foreach applicants [ ask ? [set allocated-school myself ] ;ask ? [set allocated-school myself set rankings empty-rankings ] set allocated lput ? allocated ;add this applicant to the allocated list ] set y7pupils (y7pupils + length applicants) ;set applicants [] ] ] ] set thisRank thisRank + 1 ] ;finally, for schools with unallocated places, allocate unallocated applicants by distance ;first allocated to parents of which this school is closest, then second closest etc. let thisDist 0 while[thisDist < Number-of-Schools] [ ask schools with [y7pupils < places] [ set applicants parents with [child-age = 10 and allocated-school = 0 and item thisDist distances = myself] set applicants sort-by [distance ?1 < distance ?2] applicants ifelse(length applicants > (places - y7pupils)) [ while [y7pupils < places] [ ask first applicants [ set allocated-school myself ] ;ask first applicants [ set allocated-school myself set rankings empty-rankings ] set allocated lput first applicants allocated ;add this closest applicant to the allocated list set applicants remove-item 0 applicants ;remove this closest applicant from the applicants list set y7pupils y7pupils + 1 ] ] ;if there are more places than applicants allocate all applicants a place [ without-interruption [ foreach applicants [ ask ? [set allocated-school myself ] ;ask ? [set allocated-school myself set rankings empty-rankings ] set allocated lput ? allocated ;add this applicant to the allocated list ] set y7pupils (y7pupils + length applicants) ;set applicants [] ] ] ] set thisDist thisDist + 1 ] ask schools [ set all-pupils (length y7parents + length y8parents + length y9parents + length y10parents + length y11parents) ] ask parents with [child-age = 10 ] [ set allocated-distance distance allocated-school ] end to calc-catchment-size ;calculates mean and max allocated parent distances ifelse(ticks > 0) ;initially schools have no parents [ ask schools with [school-type = "state"] [ let all-parents parents with [ allocated-school = myself ] ifelse(not any? all-parents) [ set max-distance -1 ;if no places were allocated set a no data value set max-distances lput 0 max-distances ;add the max distance to the list of max distances if(length max-distances > Parent-Memory) [ set max-distances remove-item 0 max-distances ] ;only keep track of last *Memory* years distances set mean-distance -1 ;if no places were allocated set a no data value set mean-distances lput 0 mean-distances ;add the mean distance to the list of mean distances if(length mean-distances > Parent-Memory) [ set mean-distances remove-item 0 mean-distances ] ;only keep track of last *Memory* years distances ] [ set max-distance max [allocated-distance] of all-parents ;if places were allocated find the distance of the furthest allocated parent set max-distances lput max-distance max-distances ;add the max distance to the list of max distances if(length max-distances > Parent-Memory) [ set max-distances remove-item 0 max-distances ] ;only keep track of last *Memory* years distances set mean-distance mean [allocated-distance] of all-parents ;if places were allocated find the mean distance of allocated parents set mean-distances lput mean-distance mean-distances ;add the mean distance to the list of mean distances if(length mean-distances > Parent-Memory) [ set mean-distances remove-item 0 mean-distances ] ;only keep track of last *Memory* years distances ] ] ask schools with [school-type = "new"] [ set max-distances fput (2 * world-width) max-distances set mean-distances fput (2 * world-width) mean-distances ] ] ;instead just set catchment to larger than the world [ ask schools [ set max-distances fput (2 * world-width) max-distances set mean-distances fput (2 * world-width) mean-distances ] ] end to check-success ask parents with [child-age = 10 ] [ let thisRank 0 while[thisRank < Number-of-Ranks] [ if(allocated-school = item thisRank rankings) [ set success-by-rank thisRank + 1 ] set thisRank thisRank + 1 ] if(success-by-rank != -1) [ set success-rank1 0 ] if(success-by-rank = 1) [ set success-rank1 1 ] ifelse(aspiration < [GCSE-score] of allocated-school) [ set success-by-aspiration 1 ] [ set success-by-aspiration 0 ] ] end to set-child-attainment [ yParents ] if(not empty? yParents) [ ask turtle-set yParents [ if(School-Value-Added = true) [ set child-attainment child-attainment * (1 + [value-added] of myself) ] set child-attainment (child-attainment * (1 - School-Peer-Effect - Parent-Effect)) + ([mean-attainment] of myself * School-Peer-Effect) + (aspiration * Parent-Effect) if(child-attainment > 100) [ set child-attainment 100 ] ] ] end to update-SchoolGCSE ;first update child-attainment for this year ask schools [ ;show mean-aspiration set-child-attainment y7Parents set-child-attainment y8Parents set-child-attainment y9Parents set-child-attainment y10Parents set-child-attainment y11Parents ] ;set mean and max child-attainment ask schools [ let myParents (turtle-set y7parents y8parents y9parents y10parents y11parents) ifelse(any? myParents) [ set mean-aspiration mean [aspiration] of myParents set mean-attainment mean [child-attainment] of myParents ] [ set mean-aspiration 0 set mean-attainment 0 ] ] ;only start updating GCSE-score once first cohort of allocated students has reached year 11 (before this y11Parents will be empty) if(ticks > 5) [ ask schools [ let sumAttainment 0 if(not empty? y11Parents) [ set sumAttainment sum [child-attainment] of turtle-set y11Parents set GCSE-score sumAttainment / length y11Parents if(GCSE-score > 100) [ set GCSE-score 100 ] ] ] ] ;GCSE-score is the mean of the last Parent-Memory years, just like max-distances ask schools [ set GCSE-scores lput GCSE-score GCSE-scores ;add the GCSE-scores to the list of GCSE-scores if(length GCSE-scores > Parent-Memory) [ set GCSE-scores remove-item 0 GCSE-scores ] ;only keep track of last *Memory* years distances ] ask schools [ set GCSE-score mean GCSE-scores ] end to set-SchoolCatchments ;creates a list of patches within the school catchment that are free to move into this timestep ;if this is the first tick (ticks = 0) max-distances will not have been set ifelse(ticks > 0) [ ask schools [ set catchmentPatches [] set catchmentPatches sort patches with [distance myself < min [mean-distances] of myself and not any? turtles-here] ] ] [ ask schools [ set catchmentPatches [] set catchmentPatches sort patches with [distance myself < (2 * world-width) and not any? turtles-here] ] ] end to move ask parents [ if(child-age = 10 and have-moved = false) [set want-to-move false ] ] ;don't move once child-age > 10 let movers no-turtles set movers parents with [child-age = 9 and want-to-move = true and have-moved = false] ask schools [ ifelse(Move-Closest = true) [ set catchmentPatches sort-by [ [distance myself] of ?1 < [distance myself] of ?2] catchmentPatches ] [ set catchmentPatches shuffle catchmentPatches ] ] ask movers [ let thisRank 0 while[thisRank < Number-of-Ranks] [ if(newHome = nobody) [ let thisSchool item thisRank [rankings] of self ;check if I think I am already in this school's catchment ;if so, only move if can move closer AND to a patch with greater value than current location value (but still less than my aspiration) ;no need to check other schools in rankings once this has been done... ;if not, and I am checking this school, it must be higher ranked than the school catchment I am currently in so move there regardless of patchvalue (although still less than my aspiration) if(is-agent? thisSchool and [school-type] of thisSchool != "new") ;ranking may contain non-Schools (i.e. -1 values) - do not try to move near to 'new' schools (no need as they do not allocate on distance. Also, catchment is entire world so make little point in moving anywhere within the world) [ if(not empty? [catchmentPatches] of thisSchool) ;if this school has available patches in its catchment [ ;if there is a restriction on where to move ifelse(Location-Rules = true) [ let location-value-max aspiration ;for each available patch in the school catchment, check if location-value is less than parent's aspiration let tempCatchment patch-set [catchmentPatches] of thisSchool set tempCatchment tempCatchment with [location-value < location-value-max or location-value = -1] ;if parent should maximise proximity to school ifelse(Move-Closest = true) [ if(any? tempCatchment) [ set newHome min-one-of tempCatchment [distance thisSchool] set move-target thisSchool ] ] ;else move to any patch [ if(any? tempCatchment) [ set newHome one-of tempCatchment set move-target thisSchool ] ] ] ;else move anywhere within school catchment [ ;if parent should maximise proximity to school ifelse(Move-Closest = true) [ let shortDistance 9999 ;holder for distance to closest available patch ask(thisSchool) [ set shortDistance distance first catchmentPatches ] ;if closest available patch is closer than my current position, move if(distance thisSchool > shortDistance) [ set newHome first [catchmentPatches] of thisSchool set move-target thisSchool ] ] ;else parent should move anywhere in catchment [ set newHome first [catchmentPatches] of thisSchool set move-target thisSchool ] ] if(newHome != nobody) [ ;show initialHome ask schools [ ;if(member? [newHome] of myself catchmentPatches) [ show word "removing newHome: " [newHome] of myself ] ask [newHome] of myself [if(any? parents-here) [ show "error - already a parent at new home!" ] ] set catchmentPatches remove [newHome] of myself catchmentPatches ] ask schools [ add-available-home-to-catchment [initialHome] of myself ] ] ] ] if(newHome != nobody) [ move-to newHome if(any? other parents-here) ;Error check [ let pid [who] of other parents-here show word "Error: another parent already here, agent:" pid ] set have-moved true ask(initialHome) [ set-location-value ;this works because parent can only move once. if(any? parents-here) [ show "error - still a parent here!" ] ] ] ] set thisRank thisRank + 1 ] set-parent-school-distance ;update distances list ] end to add-available-home-to-catchment [ availableHome ] let add false ifelse(ticks = 0) ;if ticks = 0, mean-distances will be empty causing an error when checked with an if statement (and catchmentPatches will contain all patches so always add when ticks = 0) [set add true ] [ if(distance availableHome < min mean-distances) [ set add true ] ] if(add) [ ;show word "adding availableHome: " availableHome set catchmentPatches sentence availableHome catchmentPatches ifelse(Move-Closest = true) [ set catchmentPatches sort-by [ [distance myself] of ?1 < [distance myself] of ?2] catchmentPatches ] [ set catchmentPatches shuffle catchmentPatches ] ] end to rank-Schools let reporter nobody ask parents with [child-age = 10 or (have-moved = false and child-age = 9)] [ ;parents calculate which catchments they are in by comparing their distance to each school with mean of last [memory] years of mean-distances set rankings [] ifelse(ticks >= 1) ;mean-distances (catchment) will not have been calculated in first step [ set catchment schools with [ distance myself < min [mean-distances] of self ] ] ;creates agentset of schools parent belives they are in the catchment for [ set catchment schools with [ distance myself < (world-width * 2) ] ] ;creates agentset of schools parent belives they are in the catchment for if(any? catchment) [ set catchment sort-by [ [GCSE-score] of ?1 > [GCSE-score] of ?2 ] catchment ] ;changes agentset to list and ranks on GCSE score (descending) set considered schools with [ GCSE-score >= [aspiration] of myself ] ;creates agentset of school parent believes are good enough if(any? considered) [ set considered sort-by [ [GCSE-score] of ?1 > [GCSE-score] of ?2 ] considered ] ;changes agentset to list and ranks on GCSE score (descending) set avoided schools with [ GCSE-score < ([aspiration] of myself * Avoided-Threshold) ] ;avoided threshold must be >0 and <1 if(Avoid-Schools = true) ;if not considering avoided schools, avoided is not changed to a list and therefore is assumed empty below [ if(any? avoided) [ set avoided sort-by [ [GCSE-score] of ?1 > [GCSE-score] of ?2 ] avoided ] ;changes agentset to list and ranks on GCSE score (descending) ] ;ranking for moving (when child-age = 9) is different for ranking for allocating (when child-age = 10) ;for moving, parent ranks solely on GCSE score (and then evaluate which school catchments they are in and whether this is acceptable) ;for allocating, parents consider GCSE score AND distance ;rank for moving ;parents try to position themselves in considered (preferred) school catchments but not in avoided school catchments ;check if I want to move (don't move if I am in a considered school catchment AND am not in an avoided school catchment) if(child-age = 9 and want-to-move = true and have-moved = false) [ let considered-present false let avoided-present false if(is-list? catchment) ;if is a list it has schools in it [ if(is-list? considered) ;if is a list it has schools in it [ foreach catchment [ if(member? ? considered and [school-type] of ? != "new") [ set considered-present true ] ] ;only consider state school catchments (will always be in the catchment of new schools which do not select on distance) ] if(is-list? avoided) ;if is a list it has schools in it [ foreach catchment [ if(member? ? avoided) [ set avoided-present true ] ] ] if(considered-present = true) [ set want-to-move false ] ;if there is a considered school in my catchment I will not move (move function will not execute if moved is true) if(avoided-present = true) [ set want-to-move true ] ;but if there is also an avoided school in my catchment, I will try to move ] ;if I still want to move if(child-age = 9 and want-to-move = true) [ ;if there are considered schools, rank considered schools on GCSE-score ifelse(is-list? considered) [ set rankings sort-by [ [GCSE-score] of ?1 > [GCSE-score] of ?2 ] considered ;considered schools will never be avoided schools ;if I want to move and avoided is a list (i.e. there is something in it) I must be in the catchment of one of the avoided schools ;so add as many non-avoided schools as possible, in descending order of GCSE score if(is-list? avoided) [ let tempSchools sort-by [ [GCSE-score] of ?1 > [GCSE-score] of ?2 ] schools ;add schools from tempSchools to end of rankings, unless it is already in rankings or is in avoided foreach tempSchools [ if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ] ] ;if there are no considered schools, rank all schools by GCSE-score but do not include avoided [ set rankings [] ;check there's nothing in rankings let tempSchools sort-by [ [GCSE-score] of ?1 > [GCSE-score] of ?2 ] schools ifelse(is-list? avoided) ;will be a list if it has something in it [ foreach tempSchools [ ;if this school is not in the avoided list, add it to the rankings list if(not member? ? avoided) [ set rankings lput ? rankings ] ] ] ;if there is nothing in avoided add all schools [ foreach tempSchools [ if(not member? ? rankings) [set rankings lput ? rankings ] ] ] ] ] ] ;rank for allocating if(child-age = 10) [ ifelse(is-agentset? catchment) ;if still an agentsent (and not converted to list) it is empty [ ifelse(is-agentset? considered) ;if still an agentsent (and not converted to list) it is empty [ ;catchment and considered are both empty (i.e. there are no schools with GCSE-score higher than my aspiration and I am not near any school) ;strategy here is to rank all schools on distance, but do not include avoided in the rankings set strategy 1 ifelse(is-list? avoided) ;will be a list if it has something in it [ set strategy 2 let tempSchools sort-by [ [distance myself] of ?1 < [distance myself] of ?2 ] schools foreach tempSchools [ ;if this school is not in the avoided list, add it to the rankings list if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ] ;if nothing in avoided add all schools to ranking based on distance [ set rankings sort-by [ [distance myself] of ?1 < [distance myself] of ?2 ] schools ] ] [ ;catchment is empty, considered is not empty (i.e. there are schools with GCSE-score higher than my aspiration and but I am not near any of them [or any school]) ;strategy here is to rank considered schools on distance, then all schools on distance but do not include avoided set strategy 3 set rankings sort-by [ [distance myself] of ?1 < [distance myself] of ?2 ] considered ;considered schools will never be avoided schools let tempSchools sort-by [ [distance myself] of ?1 < [distance myself] of ?2 ] schools ifelse(is-list? avoided) ;will be a list if it has something in it [ set strategy 4 ;add schools from tempSchools to end of rankings, unless it is already in rankings or is in avoided foreach tempSchools [ if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ] [ ;else if nothing in avoided, add tempSchools to end of rankings foreach tempSchools [ if(not member? ? rankings) [ set rankings lput ? rankings ] ] ] ] ] [ ;catchment has schools in it [always full if distance-allocation = T] ifelse(is-agentset? considered) ;if still an agentsent (and not converted to list) it is empty [ ;catchment is not empty but considered is (i.e. there are schools I will likely be allocated but I do not consider them good enough) ;strategy here is to rank catchment on GCSE-score (descending), then all other schools on distance, but do not include avoided schools ;[justfied to still rank on distance when distance-allocatin = F as parents still like their kids to go to school nearby] set strategy 5 let tempCatchment catchment ;already sorted by GCSE let tempSchools sort-by [ [distance myself] of ?1 < [distance myself] of ?2 ] schools ;reporting code for debugging ;if(reporter = nobody) ;[ ; set reporter self ; show tempCatchment ; show tempSchools ; show rankings ;] ifelse(is-list? avoided) ;will be a list if it has something in it [ set strategy 6 ;add schools from tempCatchment to rankings, unless it is in avoided foreach tempCatchment [ if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ;add schools from tempSchools to end of rankings, unless it is already in rankings or is in avoided foreach tempSchools [ if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ] ;else if nothing in avoided, add tempCatchment and tempSchools to end of rankings [ foreach tempCatchment [ if(not member? ? rankings) [ set rankings lput ? rankings ] ] foreach tempSchools [ if(not member? ? rankings) [ set rankings lput ? rankings ] ] ] ;reporting code for debugging ;if(reporter = self) ;[ ; show tempCatchment ; show tempSchools ; show rankings ;] ] [ ;neither catchment nor considered is empty ;rank catchment on GCSE-score (descending), then considered on distance, then all other schools on distance but do not include avoided set strategy 7 let tempCatchment catchment ;already sorted by GCSE let tempConsidered sort-by [ [distance myself] of ?1 < [distance myself] of ?2 ] considered let tempSchools sort-by [ [distance myself] of ?1 < [distance myself] of ?2 ] schools ifelse(is-list? avoided) ;will be a list if it has something in it [ set strategy 8 ;if this school is not in the avoided list, add it to the rankings list foreach tempCatchment [ if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ;add schools from tempConsidered to end of rankings, unless it is already in rankings or is in avoided foreach tempConsidered [ if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ;add schools from tempSchools to end of rankings, unless it is already in rankings or is in avoided foreach tempSchools [ if(not member? ? rankings and not member? ? avoided) [ set rankings lput ? rankings ] ] ] ;else if nothing in avoided, add tempRankings, tempConsidered and tempSchools to end of rankings [ foreach tempCatchment [ if(not member? ? rankings) [ set rankings lput ? rankings ] ] foreach tempConsidered [ if(not member? ? rankings) [ set rankings lput ? rankings ] ] foreach tempSchools [ if(not member? ? rankings) [ set rankings lput ? rankings ] ] ] ] ] ] if(not empty? rankings) [ ;rankings may be too long, if so remove items if(length rankings > Number-of-Ranks) [ set rankings reverse rankings ;its faster to remove from the front (and don't need to know length of rankings) while[length rankings > Number-of-Ranks] [ set rankings remove-item 0 rankings ] set rankings reverse rankings ] ] ;rankings always needs to be of length Number-of-Ranks to prevent out-of-list search in allocate-Places function (so add dummy values to fill list) if(length rankings < Number-of-Ranks) [ let thisRank length rankings while[thisRank < Number-of-Ranks] [ set rankings lput -1 rankings set thisRank thisRank + 1 ] ;set rankings empty-rankings ] ;reporting code for debugging ;if(reporter = self) ; [ ; show rankings ; set reporter true ; ] ] end to set-patch-attributes ;for ALL patches ask patches [ set location-value 0 set p-aspiration 0 set p-attainment 0 ] ask patches [ ifelse(School-Quality-Effect > 0) [ let nearestSchools sort-by [[distance myself] of ?1 < [distance myself] of ?2] schools let schoolValue [GCSE-score] of first nearestSchools let dist distance first nearestSchools ifelse(dist < (schoolRadii * 2)) [ set schoolValue (1 - ( dist / (schoolRadii * 2))^ 0.5) * schoolValue ] [ set schoolValue 0 ] ifelse(any? parents-on neighbors) [ set location-value ((mean [aspiration] of parents-on neighbors) * (1 - School-Quality-Effect)) + (schoolValue * School-Quality-Effect) ] [ set location-value 0 + (schoolValue * School-Quality-Effect) ] ] [ if(any? parents-on neighbors) [ set location-value mean [aspiration] of parents-on neighbors ] ] ] ask patches with [location-value = 0] [ print "zero location-value on neighbours" set location-value mean [location-value] of neighbors ] ask patches with [any? parents-here ] [ set p-aspiration mean [aspiration] of parents-here ;use mean to prevent run time error when checking patches without parents below set p-attainment mean [child-attainment] of parents-here ;use mean to prevent run time error when checking patches without parents below ] ask patches with [not any? parents-here] [ set p-aspiration mean [p-aspiration] of neighbors ] ask patches with [not any? parents-here] [ set p-attainment mean [p-attainment] of neighbors ] end to set-location-value ;for a SINGLE patch ifelse(School-Quality-Effect > 0) [ let nearestSchools sort-by [[distance myself] of ?1 < [distance myself] of ?2] schools let schoolValue [GCSE-score] of first nearestSchools let dist distance first nearestSchools ifelse(dist < (schoolRadii * 2)) [ set schoolValue (1 - ( dist / (schoolRadii * 2))^ 0.5) * schoolValue ] [ set schoolValue 0 ] ifelse(any? parents-on neighbors) [ set location-value ((mean [aspiration] of parents-on neighbors) * (1 - School-Quality-Effect)) + (schoolValue * School-Quality-Effect) ] [ set location-value 0 + (schoolValue * School-Quality-Effect) ] ] [ ifelse(any? parents-on neighbors) [ set location-value mean [aspiration] of parents-on neighbors ] [ set location-value mean [location-value] of neighbors ] ] end ;;---------------------------------- ;;END SIMULATION ;;---------------------------------- ;;---------------------------------- ;;PLOTTING ;;---------------------------------- to plotting do-line-plots do-bar-plots do-scatter-plots end to do-line-plots set-current-plot "GCSE-score-trend" set-current-plot-pen "max" ask max-one-of schools [GCSE-score] [ set-plot-pen-color (id * 10) + 15 plot GCSE-score ] set-current-plot-pen "mean" let mGCSE mean [GCSE-score] of schools plot mGCSE set-current-plot-pen "min" ask min-one-of schools [GCSE-score] [ set-plot-pen-color (id * 10) + 15 plot GCSE-score ] set-current-plot "Max-Distances" set-current-plot-pen "max" ask max-one-of schools [GCSE-score] [ set-plot-pen-color (id * 10) + 15 plot max-distance ] set-current-plot-pen "min" ask min-one-of schools [GCSE-score] [ set-plot-pen-color (id * 10) + 15 plot max-distance ] let mean-max-distances mean [max-distance] of schools set-current-plot-pen "mean" plot mean-max-distances set-current-plot "Mean-Distance" set-current-plot-pen "max" ask max-one-of schools [GCSE-score] [ set-plot-pen-color (id * 10) + 15 plot mean-distance ] set-current-plot-pen "min" ask min-one-of schools [GCSE-score] [ set-plot-pen-color (id * 10) + 15 plot mean-distance ] let mean-mean-distances mean [mean-distance] of schools set-current-plot-pen "mean" plot mean-mean-distances set-current-plot "Satisfaction" if(Success-Type = "ranking") [ let dcolor Number-of-Ranks / 3 ;set top third of ranks green, second third yellow, bottom third orange, unranked red if(Number-of-Ranks < 3) [ set dcolor Number-of-Ranks ] let count-green 0 let count-yellow 0 let count-orange 0 let count-red 0 let totParents count parents with [child-age = 11] ask parents with [child-age = 11] [ let thisRank 0 ;if the allocated-school was ranked ifelse(member? allocated-school rankings) [ while[thisRank < length rankings] [ if(item thisRank rankings = allocated-school) [ ifelse(thisRank < dcolor) [ set count-green count-green + 1 ] [ ifelse(thisRank < dcolor * 2) [ set count-yellow count-yellow + 1 ] [ set count-orange count-orange + 1] ] ] set thisRank thisRank + 1 ] ] ;if the allocated-school was not ranked set color red [ set count-red count-red + 1 ] ] if(ticks > 0) [ set-current-plot-pen "green" plot count-green / totParents set-current-plot-pen "yellow" plot count-yellow / totParents set-current-plot-pen "orange" plot count-orange / totParents set-current-plot-pen "red" plot count-red / totParents ] ] if(Success-Type = "aspiration") [ let count-green 0 let count-red 0 let totAlloc count parents with [allocated-school != 0] ask parents with [allocated-school != 0] [ if(aspiration > [GCSE-score] of allocated-school) [ set count-green count-green + 1 ] if(aspiration < [GCSE-score] of allocated-school) [ set count-red count-red + 1 ] ] if(ticks > 0) [ set-current-plot-pen "green" plot count-green / totAlloc set-current-plot-pen "red" plot count-red / totAlloc ] ] end to do-bar-plots set-current-plot "Application-Ratio" clear-plot set-current-plot-pen "s" set-plot-pen-color black ifelse(Ordered-Plots = false) [ ask-concurrent schools [ plotxy id app-ratio ] ] [ let tempSchools sort-by [ [app-ratio] of ?1 > [app-ratio] of ?2 ] schools foreach tempSchools [ plot [app-ratio] of ? ] ] set-current-plot "GCSE-scores" clear-plot set-current-plot-pen "s" ifelse(Ordered-Plots = false) [ ask-concurrent schools [ plotxy id GCSE-score ] ] [ let tempSchools sort-by [ [GCSE-score] of ?1 > [GCSE-score] of ?2 ] schools foreach tempSchools [ plot [GCSE-score] of ? ] ] set-current-plot "Max-Distance" clear-plot set-current-plot-pen "s" ifelse(Ordered-Plots = false) [ ask-concurrent schools [ plotxy id max-distance ] ] [ let tempSchools sort-by [ [max-distance] of ?1 > [max-distance] of ?2 ] schools foreach tempSchools [ plot [max-distance] of ? ] ] end to do-scatter-plots set-current-plot "MaxDistance-GCSE" clear-plot set-current-plot-pen "max" ask schools [ ;set-plot-pen-color (id * 10) + 15 set-plot-pen-color black plotxy GCSE-score max-distance ] set-current-plot "MaxDistance-App" clear-plot set-current-plot-pen "default" ask schools [ ;set-plot-pen-color (id * 10) + 15 set-plot-pen-color black plotxy app-ratio max-distance ] ;set-current-plot "MeanDistance-GCSE" ;clear-plot ;set-current-plot-pen "default" ;ask schools ;[ ; set-plot-pen-color (id * 10) + 15 ; plotxy GCSE-score mean-distance ;] ;set-current-plot "MeanDistance-App" ;clear-plot ;set-current-plot-pen "default" ;ask schools ;[ ; set-plot-pen-color (id * 10) + 15 ; plotxy app-ratio mean-distance ;] set-current-plot "AppRatio-GCSE" clear-plot set-current-plot-pen "default" ask schools [ ;set-plot-pen-color (id * 10) + 15 set-plot-pen-color black plotxy GCSE-score app-ratio ] if(School-Value-Added) [ set-current-plot "AppRatio-ValueAdded" clear-plot set-current-plot-pen "default" ask schools [ ;set-plot-pen-color (id * 10) + 15 set-plot-pen-color black plotxy app-ratio value-added ] ] end ;;---------------------------------- ;;END PLOTTING ;;---------------------------------- ;;---------------------------------- ;;DISPLAY ;;---------------------------------- to update-Colours let bestSchool max-one-of schools [GCSE-score] let worstSchool min-one-of schools [GCSE-score] ;show parents with specified colours ifelse(Patch-Value = false) [ ask patches [ set pcolor black ] ask parents [ set hidden? false if(Parent-Colours = "satisfaction") [ ifelse(child-age < 10 or allocated-school = 0) [ set color grey ] [ if(Success-Type = "ranking") [ let dcolor Number-of-Ranks / 3 ;set top third of ranks green, second third yellow, bottom third orange, unranked red if(Number-of-Ranks < 3) [ set dcolor Number-of-Ranks ] let thisRank 0 ;if the allocated-school was ranked ifelse(member? allocated-school rankings) [ while[thisRank < length rankings] [ if(item thisRank rankings = allocated-school) [ ifelse(thisRank < dcolor) [ set color green ] [ ifelse(thisRank < dcolor * 2) [ set color yellow ] [ set color orange ] ] ] set thisRank thisRank + 1 ] ] ;if the allocated-school was not ranked set color red [ set color red ] ] if(Success-Type = "aspiration") [ ifelse(aspiration < [GCSE-score] of allocated-school) [ set color green ] [ set color red ] ] if(Success-Type = "attainment") [ ifelse(child-attainment >= aspiration) [ set color green ] [ set color red ] ] ] ] if(Parent-Colours = "school") [ ifelse(child-age < 10 or allocated-school = 0) [ set color grey ] [ set color [id] of allocated-school * 10 + 15 ] ] if(Parent-Colours = "aspiration") [ ifelse(aspiration = 100) [ set color 19.9 ] [ set color (aspiration / 10) + 10 ] ] if(Parent-Colours = "attainment") [ ifelse(allocated-school = 0) [ set color grey ] [ ifelse(child-attainment = 100) [ set color 29.9 ] [ set color (child-attainment / 10) + 20 ] ] ] if(Parent-Colours = "attainment-change") [ ifelse(allocated-school = 0) [ set color grey ] [ let diffc child-attainment - aspiration ifelse(diffc < 0) [ ifelse(diffc = -100) [ set color 22 ] [ set color 27 - (diffc / -20) ] ] [ ifelse(diffc = 100) [ set color 62 ] [ set color 67 - (diffc / 20) ] ] ] ] if(Parent-Colours = "moved") [ ifelse(allocated-school = 0) [ set color grey ] [ ifelse(have-moved = true) [ set color green ] [ set color red ] ] ] if(Parent-Colours = "best school allocation") [ ifelse(allocated-school = 0) [ set color grey ] [ ifelse(member? bestSchool rankings) ;ifelse(item 0 rankings = bestSchool) [ ifelse(allocated-school = bestSchool) [ set color green ] [ set color red ] ] [ set color grey] ] ] if(Parent-Colours = "worst school allocation") [ ifelse(allocated-school = 0) [ set color grey ] [ ifelse(member? worstSchool rankings) ;ifelse(item 0 rankings = worstSchool) [ ifelse(allocated-school = worstSchool) [ set color green ] [ set color red ] ] [ set color grey] ] ] if(Parent-Colours = "strategy") [ ifelse(allocated-school = 0) [ set color grey ] [ set color ((strategy * 10 + 4)) ] ] if(Parent-Colours = "age") [ if(child-age = 9) [ set color 19 ] if(child-age = 10) [ set color 18 ] if(child-age = 11) [ set color 17 ] if(child-age = 12) [ set color 16 ] if(child-age = 13) [ set color 15 ] if(child-age = 14) [ set color 14 ] if(child-age = 15) [ set color 13 ] if(child-age = 16) [ set color 12 ] ] if(Parent-Colours = "allocated-distance") [ set color (allocated-distance / 8) + 122 ] ] if(Show-Unallocated = false) [ ask parents with [allocated-school = 0] [ set hidden? true ] ] if(ChildAge = "<9") [ ask parents with [child-age > 8] [ set color grey ] ] if(ChildAge = "9") [ ask parents with [child-age != 9] [ set color grey ] ] if(ChildAge = "10") [ ask parents with [child-age != 10] [ set color grey ] ] if(ChildAge = "11") [ ask parents with [child-age != 11] [ set color grey ] ] if(ChildAge = "12") [ ask parents with [child-age != 12] [ set color grey ] ] if(ChildAge = "13") [ ask parents with [child-age != 13] [ set color grey ] ] if(ChildAge = "14") [ ask parents with [child-age != 14] [ set color grey ] ] if(ChildAge = "15") [ ask parents with [child-age != 15] [ set color grey ] ] if(ChildAge = "16") [ ask parents with [child-age != 16] [ set color grey ] ] if(ChildAge = ">16") [ ask parents with [child-age < 17] [ set color grey ] ] if(ChildAge = "SchoolAge") [ ask parents with [child-age < 10 or child-age > 16 ] [ set color grey ] ] if(DistanceClass = "0-10") [ ask parents with [allocated-distance > 10] [ set color grey ] ] if(DistanceClass = "10-20") [ ask parents with [allocated-distance <= 10 or allocated-distance > 20] [ set color grey ] ] if(DistanceClass = "20-30") [ ask parents with [allocated-distance <= 20 or allocated-distance > 30] [ set color grey ] ] if(DistanceClass = "30-40") [ ask parents with [allocated-distance <= 30 or allocated-distance > 40] [ set color grey ] ] if(DistanceClass = "40-50") [ ask parents with [allocated-distance <= 40 or allocated-distance > 50] [ set color grey ] ] if(DistanceClass = "50-60") [ ask parents with [allocated-distance <= 50 or allocated-distance > 60] [ set color grey ] ] if(DistanceClass = ">60") [ ask parents with [allocated-distance <= 60 ] [ set color grey ] ] if(AspirationClass = "0-10") [ ask parents with [aspiration > 10] [ set color grey ] ] if(AspirationClass = "10-20") [ ask parents with [aspiration <= 10 or aspiration > 20] [ set color grey ] ] if(AspirationClass = "20-30") [ ask parents with [aspiration <= 20 or aspiration > 30] [ set color grey ] ] if(AspirationClass = "30-40") [ ask parents with [aspiration <= 30 or aspiration > 40] [ set color grey ] ] if(AspirationClass = "40-50") [ ask parents with [aspiration <= 40 or aspiration > 50] [ set color grey ] ] if(AspirationClass = "50-60") [ ask parents with [aspiration <= 50 or aspiration > 60] [ set color grey ] ] if(AspirationClass = "60-70") [ ask parents with [aspiration <= 60 or aspiration > 70] [ set color grey ] ] if(AspirationClass = "70-80") [ ask parents with [aspiration <= 70 or aspiration > 80] [ set color grey ] ] if(AspirationClass = "80-90") [ ask parents with [aspiration <= 80 or aspiration > 90] [ set color grey ] ] if(AspirationClass = "90-100") [ ask parents with [aspiration <= 90 or aspiration > 100] [ set color grey ] ] ] ;else don't show parents and show location value [ ask parents [ set hidden? true ] ifelse(Parent-Colours = "aspiration") [ ask patches [ ifelse(p-aspiration = 100) [ set pcolor 19.9 ] [ set pcolor (p-aspiration / 10) + 10 ] ] ] [ ask patches [ ifelse(location-value = -1) [ set pcolor black ] [ set pcolor (location-value / 10) + 10 ] ] ] ] ;always show schools let max-ratio max [app-ratio] of schools let max-value-added max [value-added] of schools let min-value-added min [value-added] of schools ask schools [ if(School-Colours = "id") [ set color (id * 10) + 15 ;first school will be red ] if(School-Colours = "GCSE") [ ifelse(GCSE-score = 100) [ set color 49.9 ] [ set color (GCSE-score / 10) + 40 ] ] if(School-Colours = "app-ratio") [ if(max-ratio != 0) [ let scaled-ratio app-ratio / max-ratio ifelse(scaled-ratio = 1) [ set color 59.9 ] [ set color (scaled-ratio * 10) + 50 ] ] ] if(School-Colours = "value-added") [ ifelse(value-added < 0) [ let scaled-va value-added / (min-value-added * 2) ifelse(scaled-va = 0.5) [ set color 80.5 ] ;don't set to 80 b/c unable to see icon on the grid [ set color 85 - (scaled-va * 10) ] ] [ let scaled-va value-added / (max-value-added * 2) ifelse(scaled-va = 0.5) [ set color 89.9 ] [ set color (scaled-va * 10) + 85 ] ] ] if(Parent-Colours = "best school allocation") [ ifelse(id != [id] of bestSchool) [ set color grey ] [ set color yellow ] ] if(Parent-Colours = "worst school allocation") [ ifelse(id != [id] of worstSchool) [ set color grey ] [ set color yellow ] ] ] if(Single-School) [ ask parents [ ifelse(allocated-school = 0) [set color grey] [ if([id] of allocated-school != Shown-School) [ set color grey ] ] ] ask schools with [id != Shown-School ] [ set color grey ] ] end ;;---------------------------------- ;;END DISPLAY ;;---------------------------------- ;;---------------------------------- ;;DATA EXPORT ;;---------------------------------- to ExportPlots let prefix "plots" let suffix ".csv" let index next-index prefix suffix let filename (word prefix index suffix) export-all-plots filename end to ExportView let prefix "interface" let suffix ".png" let index next-index prefix suffix let filename (word prefix index suffix) export-view filename end ;from TurtleZero? to-report next-index [ prefix suffix ] let index 0 let filename (word prefix index suffix ) while [ file-exists? filename ] [ set index index + 1 set filename (word prefix index suffix ) ] report index end to ExportSummaryData show "Exporting summary data" ;file-open "Schools_SummaryData.csv" let dummy "Schools_SummaryData_Exp" let suffix ".csv" let filename (word dummy exp-index suffix) file-open filename ask schools [ ;summarise y7 parents let max-distance_y7 max-one-of turtle-set y7Parents [distance myself] ifelse(max-distance_y7 = nobody) [ set max-distance_y7 -1 ] [ set max-distance_y7 distance max-distance_y7 ] let mean-distance_y7 0 let mean-aspiration_y7 0 let mean-attainment_y7 0 let parents_moved_y7 0 let parents_strategy1_y7 0 let parents_strategy2_y7 0 let parents_strategy3_y7 0 let parents_strategy4_y7 0 let parents_strategy5_y7 0 let parents_strategy6_y7 0 let parents_strategy7_y7 0 let parents_strategy8_y7 0 let success-aspiration 0 foreach y7Parents [ set mean-distance_y7 mean-distance_y7 + distance ? set mean-aspiration_y7 mean-aspiration_y7 + [aspiration] of ? set mean-attainment_y7 mean-attainment_y7 + [child-attainment] of ? if([have-moved] of ? = true) [ set parents_moved_y7 parents_moved_y7 + 1 ] if([strategy] of ? = 1) [ set parents_strategy1_y7 parents_strategy1_y7 + 1 ] if([strategy] of ? = 2) [ set parents_strategy2_y7 parents_strategy2_y7 + 1 ] if([strategy] of ? = 3) [ set parents_strategy3_y7 parents_strategy3_y7 + 1 ] if([strategy] of ? = 4) [ set parents_strategy4_y7 parents_strategy4_y7 + 1 ] if([strategy] of ? = 5) [ set parents_strategy5_y7 parents_strategy5_y7 + 1 ] if([strategy] of ? = 6) [ set parents_strategy6_y7 parents_strategy6_y7 + 1 ] if([strategy] of ? = 7) [ set parents_strategy7_y7 parents_strategy7_y7 + 1 ] if([strategy] of ? = 8) [ set parents_strategy8_y7 parents_strategy8_y7 + 1 ] if(GCSE-score < [aspiration] of ?) [ set success-aspiration success-aspiration + 1 ] ] ifelse(length y7Parents > 0) [ set mean-distance_y7 mean-distance_y7 / length y7Parents set mean-aspiration_y7 mean-aspiration_y7 / length y7Parents set mean-attainment_y7 mean-attainment_y7 / length y7Parents ] [ set mean-distance_y7 -1 set mean-aspiration_y7 -1 set mean-attainment_y7 -1 ] ;summarise y11 parents let max-distance_y11 max-one-of turtle-set y11Parents [distance myself] ifelse(max-distance_y11 = nobody) [ set max-distance_y11 -1 ] [ set max-distance_y11 distance max-distance_y11 ] let mean-distance_y11 0 let mean-aspiration_y11 0 let mean-attainment_y11 0 let success-attainment 0 foreach y11Parents [ set mean-distance_y11 mean-distance_y11 + distance ? set mean-aspiration_y11 mean-aspiration_y11 + [aspiration] of ? set mean-attainment_y11 mean-attainment_y11 + [child-attainment] of ? if([child-attainment] of ? > [aspiration] of ?) [ set success-attainment success-attainment + 1 ] ] ifelse(length y11Parents > 0) [ set mean-distance_y11 mean-distance_y11 / length y11Parents set mean-aspiration_y11 mean-aspiration_y11 / length y11Parents set mean-attainment_y11 mean-attainment_y11 / length y11Parents ] [ set mean-distance_y11 -1 set mean-aspiration_y11 -1 set mean-attainment_y11 -1 ] let mean-attainment_change_y11 0 let count-attainment_change+_y11 0 let count-attainment_change-_y11 0 ask turtle-set y11Parents [ let my-attainment-change child-attainment - aspiration set mean-attainment_change_y11 mean-attainment_change_y11 + my-attainment-change ifelse(my-attainment-change > 0) [ set count-attainment_change+_y11 count-attainment_change+_y11 + 1 ] [ set count-attainment_change-_y11 count-attainment_change-_y11 + 1 ] ] ifelse(length y11Parents > 0) [ set mean-attainment_change_y11 mean-attainment_change_y11 / length y11Parents ] [ set mean-attainment_change_y11 -1 ] let unallocated [] let all-applicants-list sort all-applicants foreach all-applicants-list [ if(not member? ? allocated) [set unallocated lput ? unallocated] ] let max-distance_unallocated max-one-of turtle-set unallocated [distance myself] ifelse(max-distance_unallocated = nobody) [ set max-distance_unallocated -1 ] [ set max-distance_unallocated distance max-distance_unallocated ] let mean-aspiration_unallocated 0 let mean-distance_unallocated 0 foreach unallocated [ set mean-aspiration_unallocated mean-aspiration_unallocated + [aspiration] of ? set mean-distance_unallocated mean-distance_unallocated + distance ? ] ifelse(length unallocated > 0) [ set mean-aspiration_unallocated mean-aspiration_unallocated / length unallocated set mean-distance_unallocated mean-distance_unallocated / length unallocated ] [ set mean-aspiration_unallocated -1 set mean-distance_unallocated -1 ] let myRanks [ 0 0 0 0 0 0 ] ask turtle-set allocated [ let thisRank 0 if(length rankings > 1) [ while[thisRank < Number-of-Ranks] [ if(item thisRank rankings = myself) [ set myRanks replace-item thisRank myRanks (item thisRank myRanks + 1) ] set thisRank thisRank + 1 ] ] ] let parents_rank1_y7 item 0 myRanks let parents_rank2_y7 item 1 myRanks let parents_rank3_y7 item 2 myRanks let parents_rank4_y7 item 3 myRanks let parents_rank5_y7 item 4 myRanks let parents_rank6_y7 item 5 myRanks let parents_unranked_y7 0 ask turtle-set allocated [ if(not member? myself rankings) [ set parents_unranked_y7 parents_unranked_y7 + 1 ] ] let parents_avoiding_y7 0 ask parents with [child-age = 11] [ if(member? myself avoided) [ set parents_avoiding_y7 parents_avoiding_y7 + 1 ] ] file-type ticks file-type "," file-type id file-type "," file-type school-type file-type "," file-type xcor file-type "," file-type ycor file-type "," file-type all-pupils file-type "," file-type precision value-added 2 file-type "," file-type precision GCSE-score 2 file-type "," file-type precision app-ratio 2 file-type "," file-type precision max-distance_y7 2 file-type "," file-type precision max-distance_y11 2 file-type "," file-type precision max-distance_unallocated 2 file-type "," file-type precision mean-distance_y7 2 file-type "," file-type precision mean-distance_y11 2 file-type "," file-type precision mean-distance_unallocated 2 file-type "," file-type precision mean-aspiration_y7 2 file-type "," file-type precision mean-aspiration_y11 2 file-type "," file-type precision mean-aspiration_unallocated 2 file-type "," file-type precision mean-attainment_y7 2 file-type "," file-type precision mean-attainment_y11 2 file-type "," file-type precision parents_rank1_y7 2 file-type "," file-type precision parents_rank2_y7 2 file-type "," file-type precision parents_rank3_y7 2 file-type "," file-type precision parents_rank4_y7 2 file-type "," file-type precision parents_rank5_y7 2 file-type "," file-type precision parents_rank6_y7 2 file-type "," file-type precision parents_unranked_y7 2 file-type "," file-type precision success-aspiration 2 file-type "," file-type precision success-attainment 2 file-type "," file-type precision parents_avoiding_y7 2 file-type "," file-type precision parents_moved_y7 2 file-type "," file-type precision mean-attainment_change_y11 2 file-type "," file-type precision count-attainment_change+_y11 2 file-type "," file-type precision count-attainment_change-_y11 2 file-type "," file-type precision parents_strategy1_y7 2 file-type "," file-type precision parents_strategy2_y7 2 file-type "," file-type precision parents_strategy3_y7 2 file-type "," file-type precision parents_strategy4_y7 2 file-type "," file-type precision parents_strategy5_y7 2 file-type "," file-type precision parents_strategy6_y7 2 file-type "," file-type precision parents_strategy7_y7 2 file-type "," file-print precision parents_strategy8_y7 2 ] file-close ;file-open "Parents_Data.csv" set dummy "Parents_Data_Exp" set filename (word dummy exp-index suffix) file-open filename ask parents [ file-type ticks file-type "," file-type who file-type "," file-type xcor file-type "," file-type ycor file-type "," file-type precision aspiration 2 file-type "," file-type child-age file-type "," ifelse(allocated-school != 0) [ file-type [id] of allocated-school file-type "," file-type precision allocated-distance 2 ;07Sept12 moved this line here from next ifelse to ensure distance is always output file-type "," ifelse(is-turtle? first rankings) [ file-type [id] of first rankings file-type "," ] [ file-type -1 file-type "," ] file-type success-by-rank file-type "," file-type success-rank1 file-type "," file-type precision child-attainment 2 file-type "," file-type strategy file-type "," ifelse(have-moved) [ file-print 1 ] [ file-print 0 ] ] [ file-type -1 file-type "," file-type -1 file-type "," file-type -1 file-type "," file-type -1 file-type "," file-type -1 file-type "," file-type -1 file-type "," file-type -1 file-type "," file-print -1 ] ] file-close ;file-open "World_SummaryData.csv" set dummy "World_SummaryData_Exp" set filename (word dummy exp-index suffix) file-open filename file-type ticks file-type "," file-type mean [GCSE-score] of schools file-type "," file-type ((max [GCSE-score] of schools) - (min [GCSE-score] of schools)) file-type "," file-type mean [app-ratio] of schools file-type "," file-type ((max [app-ratio] of schools) - (min [app-ratio] of schools)) file-type "," file-type asp-moran-i file-type "," file-type asp-moran-i-p file-type "," file-type att-moran-i file-type "," file-type att-moran-i-p file-type "," file-type GA-m file-type "," file-type GA-r file-type "," file-type GA-p file-type "," file-type GMx-m file-type "," file-type GMx-r file-type "," file-type GMx-p file-type "," file-type GMn-m file-type "," file-type GMn-r file-type "," file-type GMn-p file-type "," file-type AMx-m file-type "," file-type AMx-r file-type "," file-type AMx-p file-type "," file-type AMn-m file-type "," file-type AMn-r file-type "," file-print AMn-p file-close end to ExportSummaryData_header show "Exporting summary data" let dummy "Schools_SummaryData_Exp" let suffix ".csv" let filename (word dummy exp-index suffix) file-open filename write-experiment-data file-print "Tick,School_id,school-type,school-x-cor,school-y-cor,all-pupils,Value-Added,GCSE-score,App-ratio,max-distance_y7,max-distance_y11,max-distance_unallocated,mean-distance_y7,mean-distance_y11,mean-distance_unallocated,mean-aspiration_y7,mean-aspiration_y11,mean-aspiration_unallocated,mean-attainment_y7,mean-attainment_y11,parents_rank1_y7,parents_rank2_y7,parents_rank3_y7,parents_rank4_y7,parents_rank5_y7,parents_rank6_y7,parents_unranked_y7,success-aspiration_y7,success-attainment_y11,parents_avoiding_y7,parents_moved_y7,mean-attainment_change_y11,count-attainment_change+_y11,count-attainment_change-_y11,parents_strategy1_y7,parents_strategy2_y7,parents_strategy3_y7,parents_strategy4_y7,parents_strategy5_y7,parents_strategy6_y7,parents_strategy7_y7,parents_strategy8_y7" file-close set dummy "Parents_Data_Exp" set filename (word dummy exp-index suffix) file-open filename file-print word "Date/time: " date-and-time file-print "Tick,parent,x-cor,y-cor,aspiration,child-age,allocated-school,allocated-distance,preferred-school,allocated-rank,success-rank1,child-attainment,strategy,have-moved" file-close set dummy "World_SummaryData_Exp" set filename (word dummy exp-index suffix) file-open filename write-experiment-data file-print "Tick,MeanGCSE,RangeGCSE,MeanAppRatio,RangeAppRatio,asp-moran-i,asp-moran-i-p,pv-moran-i,pv-moran-i-p,GA-m,GA-r,GA-p,GMx-m,GMx-r,GMx-p,GMn-m,GMn-r,GMn-p,AMx-m,AMx-r,AMx-p,AMn-m,AMn-r,AMn-p" file-close end to write-experiment-data ;FILE MUST ALREADY BE OPEN! file-print word "Date/time: " date-and-time file-print word "seed," seed file-print word "Families," Families file-print word "Parent-Memory," Parent-Memory file-print word "SchoolSize," SchoolSize file-print word "Number-of-Schools," Number-of-Schools file-print word "Departure-Probability," 1 file-print word "Number-of-Ranks," Number-of-Ranks file-print word "Random-Schools," Random-Schools file-print word "Min-School-Spacing," Min-School-Spacing file-print word "Initial-School-GCSE-Distribution," Initial-School-GCSE-Distribution file-print word "School-Value-Added," School-Value-Added file-print word "Parent-Aspiration-Distribution," Parent-Aspiration-Distribution file-print word "Aspiration-Mean," Aspiration-Mean file-print word "School-Value-Added-Distribution," School-Value-Added-Distribution file-print word "Location-Rules," Location-Rules file-print word "Move-Closest," Move-Closest file-print word "Avoid-Schools," Avoid-Schools file-print word "Avoided-Threshold," Avoided-Threshold file-print word "School-Peer-Effect," School-Peer-Effect file-print word "School-Quality-Effect," School-Quality-Effect file-print word "Parent-Effect," Parent-Effect file-print word "Attainment=Aspiration?," attainment=aspiration? end to ExportWorldData show "Exporting world data" let dummy "World_Exp" let filename (word dummy exp-index "_Tick" ticks ".csv") export-world filename let cmd (word "C:\\Program Files\\WinRAR\\WinRAR.exe\" A -dr -ep -ibck " directory "\\" "World_tick" ticks ".rar " directory "\\" filename) ;show cmd show shell:exec cmd end to ExportWorldData_initial show "Exporting world data" let filename (word "World_Exp" exp-index "_Tick_initial.csv") export-world filename let cmd (word "C:\\Program Files\\WinRAR\\WinRAR.exe\" A -dr -ep -ibck " directory "\\" "World_tick_initial.rar " directory "\\" filename) ;show cmd show shell:exec cmd end to ZipParents_Data let filename (word "Parents_Data_Exp" exp-index ".csv") let cmd (word "C:\\Program Files\\WinRAR\\WinRAR.exe\" A -dr -ep -ibck " directory "\\" "Parents_Data.rar " directory "\\" filename) show shell:exec cmd end to export-worldview show "Exporting world view" let filename (word "WorldView_Exp" exp-index "_Tick" ticks ".png") export-view filename end ;;---------------------------------- ;;END DATA EXPORT ;;---------------------------------- ;;---------------------------------- ;;DATA IMPORT ;;---------------------------------- to import ;Jul12 - this needs to be updated to reflect recent changes ;; (for this model to work with NetLogo's new plotting features, ;; __clear-all-and-reset-ticks should be replaced with clear-all at ;; the beginning of your setup procedure and reset-ticks at the end ;; of the procedure.) __clear-all-and-reset-ticks random-seed seed set schoolRadii sqrt((SchoolSize * 5) / pi) if(Random-Schools = false) [ set Families 100 set SchoolSize 100 set Number-of-Schools 9 ] setup-Parents setup-Schools ;setup-Patches plotting import-world user-file end ;;---------------------------------- ;;END DATA IMPORT ;;---------------------------------- ;;---------------------------------- ;;STATS ;;---------------------------------- to setup-R print "setting up R" r:clear r:eval("library(spdep)") r:put "nrow" world-height r:put "ncol" world-width let corner-d 100 ask patch max-pxcor max-pycor [ set corner-d distancexy min-pxcor min-pycor] ifelse(corner-d < 2) [ r:eval("grid.nb <- cell2nb(nrow, ncol, type='queen', torus=TRUE)") ] [ r:eval("grid.nb <- cell2nb(nrow, ncol, type='queen', torus=FALSE)") ] r:eval("grid.listw <- nb2listw(grid.nb, style='C')") set asp-moran-i 0 set asp-moran-i-p 0 set att-moran-i 0 set att-moran-i-p 0 set GA-m 0 set GA-r 0 set GA-p 0 set GMx-m 0 set GMx-r 0 set GMx-p 0 set GMn-m 0 set GMn-r 0 set GMn-p 0 set AMx-m 0 set AMx-r 0 set AMx-p 0 set AMn-m 0 set AMn-r 0 set AMn-p 0 end to calc-Moran ;17Jul12 ;need to use patch attribute values for spatial autocorrelation (b/c using cell2nb in R to deal with toroid) ifelse(calc-Moran? and ticks >= 20) ;ticks >= 20 to speed execution time for analysis [ print "calc Moran's I (R)" ;aspiration r:put "p.aspiration" map [[p-aspiration] of ?] sort patches ;print map [[p-aspiration] of ?] sort patches r:eval("asp.i <- moran.test(p.aspiration, grid.listw)") set asp-moran-i r:get("asp.i$estimate[1]") set asp-moran-i-p r:get("asp.i$p.value") print word "Moran's i (aspiration): " asp-moran-i print word "Moran's i, p-value: " asp-moran-i-p ;r:setPlotDevice ;r:eval("moran.plot(p.aspiration, grid.listw)") ;attain r:put "p.attainment" map [[p-attainment] of ?] sort patches ;print map [[p-attainment] of ?] sort patches r:eval("att.i <- moran.test(p.attainment, grid.listw)") set att-moran-i r:get("att.i$estimate[1]") set att-moran-i-p r:get("att.i$p.value") print word "Moran's i (attainment): " att-moran-i print word "Moran's i, p-value: " att-moran-i-p ;r:setPlotDevice ;r:eval("moran.plot(p.attainment, grid.listw)") ] [ ;create dummy values set asp-moran-i -99 set asp-moran-i-p -99 set att-moran-i -99 set att-moran-i-p -99 ] end to calc-relationships print "calc relationships (R)" r:put "sGCSEs" map [ [GCSE-score] of ? ] sort schools r:put "sAppRatios" map [ [app-ratio] of ? ] sort schools r:put "sMaxDists" map [ [max-distance] of ? ] sort schools r:put "sMeanDists" map [ [mean-distance] of ? ] sort schools r:eval("dat <- cbind(sGCSEs, sAppRatios, sMaxDists, sMeanDists)") r:eval("dat <- as.data.frame(dat)") r:eval("GCSEvsAppRatioLM <- lm(sGCSEs ~ sAppRatios, data = dat)") r:eval("GCSEvsMaxDistLM <- lm(sGCSEs ~ sMaxDists, data = dat)") r:eval("GCSEvsMeanDistLM <- lm(sGCSEs ~ sMeanDists, data = dat)") r:eval("AppRatiovsMaxDistLM <- lm(sAppRatios ~ sMaxDists, data = dat)") r:eval("AppRatiovsMeanDistLM <- lm(sAppRatios ~ sMeanDists, data = dat)") set GA-m r:get("summary(GCSEvsAppRatioLM)$coefficients[2]") set GA-r r:get("summary(GCSEvsAppRatioLM)$r.squared") set GA-p r:get("anova(GCSEvsAppRatioLM)$'Pr(>F)'[1]") set GMx-m r:get("summary(GCSEvsMaxDistLM)$coefficients[2]") set GMx-r r:get("summary(GCSEvsMaxDistLM)$r.squared") set GMx-p r:get("anova(GCSEvsMaxDistLM)$'Pr(>F)'[1]") set GMn-m r:get("summary(GCSEvsMeanDistLM)$coefficients[2]") set GMn-r r:get("summary(GCSEvsMeanDistLM)$r.squared") set GMn-p r:get("anova(GCSEvsMeanDistLM)$'Pr(>F)'[1]") set AMx-m r:get("summary(AppRatiovsMaxDistLM)$coefficients[2]") set AMx-r r:get("summary(AppRatiovsMaxDistLM)$r.squared") set AMx-p r:get("anova(AppRatiovsMaxDistLM)$'Pr(>F)'[1]") set AMn-m r:get("summary(AppRatiovsMeanDistLM)$coefficients[2]") set AMn-r r:get("summary(AppRatiovsMeanDistLM)$r.squared") set AMn-p r:get("anova(AppRatiovsMeanDistLM)$'Pr(>F)'[1]") end ;;---------------------------------- ;;END STATS ;;----------------------------------

There is only one version of this model, created over 11 years ago by James Millington.

## Attached files

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

Aspiration, Attainment and Success (JASSS 2013).png | preview | Preview for 'Aspiration, Attainment and Success (JASSS 2013)' | over 11 years ago, by James Millington | Download |

This model does not have any ancestors.

This model does not have any descendants.