Gender indicators 3.4 3.5

Indicators/gender-CC-3-4/CC.3.4 SPSS Syntax.sps

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+* Encoding: UTF-8.
+*Variables Labels and Coding.
+*ENUgenEntity Variable.
+VARIABLE LABELS 
+ENUGenEntityYN "Does a WFP food assistance decision-making entity exist, and are one or more members present at the site? ".
+VARIABLE LABELS
+RGenEntityYN  "Are you a member of, or do you participate in one or more of the following entities? Food distribution related entity, nutrition-related entity,  farmer group or related, school feeding related entity, climate change or disaster risk reduction related entity or any other entity".
+
+VALUE LABELS 
+ENUGenEntityYN RGenEntityYN 0 "No" 1 "Yes".
+EXECUTE.
+
+*RGenEntityYN Variable.
+
+VALUE LABELS
+RGenEntityYN 0 "No" 1 "Yes". 
+EXECUTE.
+
+
+
+* Define binary variables for each entity type.
+COMPUTE Entity_FoodDist = (RGenEntityType = 1).
+COMPUTE Entity_Nutrition = (RGenEntityType = 2).
+COMPUTE Entity_FarmerGroup = (RGenEntityType = 3).
+COMPUTE Entity_SchoolFeeding = (RGenEntityType = 4).
+COMPUTE Entity_ClimateChange = (RGenEntityType = 5).
+COMPUTE Entity_Other = (RGenEntityType = 999).
+EXECUTE.
+
+* Label the new variables.
+VARIABLE LABELS Entity_FoodDist "Food distribution related entity".
+VARIABLE LABELS Entity_Nutrition "Nutrition-related entity".
+VARIABLE LABELS Entity_FarmerGroup "Farmer group or related".
+VARIABLE LABELS Entity_SchoolFeeding "School feeding related entity".
+VARIABLE LABELS Entity_ClimateChange "Climate change or disaster risk reduction related entity".
+VARIABLE LABELS Entity_Other "Other (Specify)".
+EXECUTE.
+
+* Assign value labels.
+VALUE LABELS Entity_FoodDist Entity_Nutrition Entity_FarmerGroup Entity_SchoolFeeding Entity_ClimateChange Entity_Other
+    0 "No"
+    1 "Yes".
+EXECUTE.
+
+*Other entity.
+VARIABLE LABELS
+RGenEntityType_oth "Other (Specify)".
+EXECUTE.
+
+*Sex of the respondent.
+VARIABLE LABELS
+RESPSex	"Sex of the Respondent".
+VALUE LABELS
+RESPSex	0 "Female" 1 "Male".
+EXECUTE.
+
+*Age of the respondent.
+VARIABLE LABELS
+RESPAge "What is your age in years?".
+EXECUTE.
+
+*Disability questions.
+*Seeing.
+VARIABLE LABELS
+RDisabSee "Do you have difficulty seeing, even if wearing glasses?".
+*Hearing.
+VARIABLE LABELS
+RDisabHear "Do you have difficulty hearing, even if using a hearing aid(s)?".
+*Walking.
+VARIABLE LABELS
+RDisabWalk	"Do you have difficulty walking or climbing steps?".
+*Remember.
+VARIABLE LABELS
+RDisabRemember	"Do you have difficulty remembering or concentrating?".
+*Understanding.
+VARIABLE LABELS
+RDisabUnderstand	"Using your usual language, do you have difficulty communicating, for example understanding or being understood?".
+*Wash.
+VARIABLE LABELS
+RDisabWash	"Do you have difficulty with self-care, such as washing all over or dressing?".
+
+
+VALUE LABELS 
+RDisabSee RDisabHear RDisabWalk RDisabRemember RDisabUnderstand	RDisabWash 1	"No difficulty"2 "Some difficulty" 3 "A lot of difficulty" 4 "Cannot do at all" 888	"Don’t know" 999 "Refuse".
+EXECUTE.
+
+
+
+*When was the last time you participated in the entity?.
+VARIABLE LABELS
+RGenEntityDate	"When was the last time you participated in the entity?".
+VALUE LABELS
+RGenEntityDate 1	"Less than a week" 2  "Less than a month" 3  "Between one and three months" 4 "More than three months" 888	"Don’t know" 999  "Refuse".
+EXECUTE.
+
+
+**Meaningful Participation Questions.
+*Participation info.
+VARIABLE LABELS
+RGenEntityInf	"The last time you participated in the entity, were you informed about an intervention's update, your rights, responsibilities, or options (related to the entity´s mandate, project ongoing or about to start…)?".
+*Consulted through the meeting.
+VARIABLE LABELS
+RGenEntityCon	"The last time you participated in the entity, were you consulted through meetings or other means (interviews, surveys…)  about a new initiative, a challenge, or a new plan?".
+*were you asked to put your opinion.
+VARIABLE LABELS
+RGenEntityPla	"The last time you participated in the entity, were you informed and consulted but your opinion was not reflected in final decisions?".
+*were you able to negotiate?.
+VARIABLE LABELS
+RGenEntityNeg	"The last time you participated in the entity, could you negotiate with the decision makers on decisions that would affect you?".
+*The last time you participated in the entity, did decision makers negotiate with you to ensure viability of a project, intervention or to address an important issue?.
+VARIABLE LABELS
+RGenEntityDel	"The last time you participated in the entity, did decision makers negotiate with you to ensure viability of a project, intervention or to address an important issue?".
+*were you a decision maker?.
+VARIABLE LABELS
+RGenEntityDM	"The last time you participated in the entity, were you a decision-maker?".
+VALUE LABELS
+RGenEntityInf RGenEntityCon RGenEntityPla RGenEntityNeg RGenEntityDel RGenEntityDM 1 "Yes" 2 "No".
+EXECUTE.
+
+
+**--------------------------------------------------------------------------------------------------------------------------------------------------------**
+* Create the variable CC.3.4: Meaningful participation in WFP-supported entities at the community level*
+**--------------------------------------------------------------------------------------------------------------------------------------------------------**
+** make sure to apply pre-conditions of questions 1 and 2**.
+** Filter for the Year K.
+*====================================================================================*
+***Proportion of women in decision-making entities who report a meaningful participation in year k
+*====================================================================================*
+  * Step 1: Identify women reporting meaningful participation (G1). 
+COMPUTE G1 =(ENUGenEntityYN = 1 AND RGenEntityYN =1) AND ( RGenEntityNeg = 1 |  RGenEntityDel = 1 | RGenEntityDM = 1) AND RESPSex = 0. 
+* Step 2: Identify women in decision-making entities (i). 
+COMPUTE i = (ENUGenEntityYN = 1 AND RGenEntityYN =1 AND RESPSex= 0). 
+EXECUTE.
+
+VARIABLE LABELS 
+G1 "Women reporting meaningful participation in decision making entities".
+VARIABLE LABELS
+i "Number of women who confirm they are members of or participants in decision-making entities".
+EXECUTE.
+
+* Step 3: Count the number of cases where G1 = 1 and i = 1.
+COUNT Sum_G1 = G1 (1).
+COUNT Sum_i = i (1).
+EXECUTE.
+
+* Step 4: Calculate the proportion of Sum_G1 divided by Sum_i.
+COMPUTE Proportion_Women_Meaningful_Participation = (Sum_G1 / Sum_i) * 100.
+VALUE LABELS Proportion_Women_Meaningful_Participation 0 "No meaningful participation" 100 "Meaningful Participation".
+EXECUTE.
+
+* Step 5: Display the computed results ** TAKE VALID PERCENT VALUE*.
+FREQUENCIES VARIABLES=Sum_G1 Sum_i Proportion_Women_Meaningful_Participation
+  /STATISTICS=MEAN SUM
+  /ORDER=ANALYSIS.
+
+*====================================================================================*
+***Proportion of men in decision-making entities who report a meaningful participation in year k
+*====================================================================================*
+  * Step 1: Identify men reporting meaningful participation (G2). 
+COMPUTE G2 = (ENUGenEntityYN = 1 AND RGenEntityYN =1) AND ( RGenEntityNeg = 1 |  RGenEntityDel = 1 | RGenEntityDM = 1) AND RESPSex = 1. 
+* Step 2: Identify men  in decision-making entities (j). 
+COMPUTE j = (ENUGenEntityYN = 1 AND RGenEntityYN =1) AND RESPSex= 1. 
+EXECUTE.
+
+VARIABLE LABELS 
+G2 "Men reporting meaningful participation in decision making entities".
+VARIABLE LABELS
+j "Number of men who confirm they are members of or participants in decision-making entities".
+EXECUTE.
+
+* Step 3: Count the number of cases where G2 = 1 and j= 1.
+COUNT Sum_G2 = G2 (1).
+COUNT Sum_j = j (1).
+EXECUTE.
+
+* Step 4: Calculate the proportion of Sum_G2 divided by Sum_j.
+COMPUTE Proportion_men_Meaningful_Participation = (Sum_G2 / Sum_j) * 100.
+VALUE LABELS Proportion_men_Meaningful_Participation 0 "No meaningful participation" 100 "Meaningful Participation".
+EXECUTE.
+
+* Step 5: Display the computed results ** TAKE VALID PERCENT VALUE*.
+FREQUENCIES VARIABLES=Sum_G2 Sum_j Proportion_men_Meaningful_Participation
+  /STATISTICS=MEAN SUM
+  /ORDER=ANALYSIS.
+
+**================Create a new variable for disabled people 1= has disability 0= does not have a disability======*.
+
+COMPUTE Disabled= (RDisabSee>= 3 |  RDisabHear >= 3 |  RDisabWalk>=3 |  RDisabRemember>= 3 | RDisabUnderstand >= 3 | RDisabWash >= 3).
+EXECUTE.
+VALUE LABELS Disabled 1"has disability" 0 "does not have a disability".
+
+
+*====================================================================================*
+***Proportion of women living with disabilities in decision-making entities who report a meaningful participation in year k
+*====================================================================================*
+**Identify women with disabilities reporting meaningful participation  decision making entities*.
+*=====================================================================================*.
+*=====================================================================================*.
+  * Step 1: Identify disabled women reporting meaningful participation (G3). 
+COMPUTE G3= (ENUGenEntityYN = 1 AND RGenEntityYN =1) AND Disabled=1  AND ( RGenEntityNeg = 1 |  RGenEntityDel = 1 | RGenEntityDM = 1) AND  RESPSex= 0.
+EXECUTE.
+*====================================================================================*
+**Step 2: Identify women with disabilities who are members in decision making entities*
+*=====================================================================================*.
+COMPUTE m =  (ENUGenEntityYN = 1 AND RGenEntityYN =1) AND Disabled=1  AND RESPSex= 0. 
+EXECUTE. 
+
+VARIABLE LABELS
+G3 "Women living with disabilities reporting meaningful participation in decision-making entities".
+VARIABLE LABELS
+m "Number of women living with disabilities who confirm they are members of or participants in decision-making entities".
+
+* Step 3: Count the number of cases where G3= 1 and m = 1.
+COUNT Sum_G3 = G3 (1).
+COUNT Sum_m = m (1).
+EXECUTE.
+
+* Step 4: Calculate the proportion of Sum_G3 divided by Sum_m.
+COMPUTE Proportion_Disabled_Women_Meaningful_Participation = (Sum_G3 / Sum_m) * 100.
+VALUE LABELS Proportion_Disabled_Women_Meaningful_Participation 0 "No meaningful participation" 100 "Meaningful Participation".
+EXECUTE.
+
+* Step 5: Display the computed results ** TAKE VALID PERCENT VALUE*.
+** to remove missing cases found when dividing by zero, use select IF first**.
+*SELECT IF (NOT MISSING(Proportion_Disabled_Women_Meaningful_Participation)).  
+
+FREQUENCIES VARIABLES=Sum_G3 Sum_m Proportion_Disabled_Women_Meaningful_Participation
+  /STATISTICS=MEAN SUM
+  /ORDER=ANALYSIS.
+
+* Another way of displaying the results but in a different dataset window, Aggregate data to sum G3 and m then calculate the indicator. 
+
+AGGREGATE 
+  /OUTFILE=*  /* Keeps the aggregated data in the current dataset */ 
+  /BREAK=  /* Leave this blank if not grouping by any variables */ 
+  /Sum_G3 = SUM(G3) 
+  /Sum_m= SUM(m). 
+COMPUTE Proportion_Women_Disability_Meaningful_Participation = (Sum_G3 / Sum_m) * 100. 
+EXECUTE.
+
+
+*====================================================================================*
+***Proportion of men living with disabilities in decision-making entities who report a meaningful participation in year k
+*====================================================================================*
+** Step 1: Identify men with disabilities reporting meaningful participation  decision making entities*.
+
+*=====================================================================================*.
+COMPUTE G4= (ENUGenEntityYN = 1 AND RGenEntityYN =1)  AND Disabled=1 AND ( RGenEntityNeg = 1 |  RGenEntityDel = 1 | RGenEntityDM = 1) AND  RESPSex= 1.
+EXECUTE.
+*====================================================================================*
+** Step 2: Identify men with disabilities who are members in decision making entities*
+*=====================================================================================*.
+COMPUTE  p =  (ENUGenEntityYN = 1 AND RGenEntityYN =1) AND Disabled=1 AND RESPSex= 1. 
+EXECUTE. 
+
+VARIABLE LABELS
+G4 "Men living with disabilities reporting meaningful participation in decision-making entities".
+VARIABLE LABELS
+p "Number of men living with disabilities who confirm they are members of or participants in decision-making entities".
+
+* Step 3: Count the number of cases where G4= 1 and p = 1.
+COUNT Sum_G4 = G4 (1).
+COUNT Sum_p = p (1).
+EXECUTE.
+
+* Step 4: Calculate the proportion of Sum_G3 divided by Sum_m.
+COMPUTE Proportion_Disabled_men_Meaningful_Participation = (Sum_G4 / Sum_p) * 100.
+VALUE LABELS Proportion_Disabled_men_Meaningful_Participation 0 "No meaningful participation" 100 "Meaningful Participation".
+EXECUTE.
+
+* Step 5: Display the computed results ** TAKE VALID PERCENT VALUE*.
+** to remove missing cases found when dividing by zero, use select IF first**.
+*SELECT IF (NOT MISSING(Proportion_Disabled_men_Meaningful_Participation)).  
+
+FREQUENCIES VARIABLES=Sum_G4 Sum_p Proportion_Disabled_men_Meaningful_Participation
+  /STATISTICS=MEAN SUM
+  /ORDER=ANALYSIS.
+
+* another way of displaying the results but in a separate dataset window, Aggregate data to sum G4 and p then calculate the indicator. 
+
+AGGREGATE 
+  /OUTFILE=*  /* Keeps the aggregated data in the current dataset */ 
+  /BREAK=  /* Leave this blank if not grouping by any variables */ 
+  /Sum_G4 = SUM(G4) 
+  /Sum_p= SUM(p). 
+COMPUTE Proportion_Men_Disability_Meaningful_Participation = (Sum_G4 / Sum_p) * 100. 
+EXECUTE.
+
+
+**=======================================================================================*
+***Proportion of women in decision-making entities who report being the decision maker
+**=======================================================================================*.
+
+  * Step 1: Identify  women being the decision maker (G5).
+
+COMPUTE G5= (ENUGenEntityYN = 1 AND RGenEntityYN =1) AND RGenEntityDM=1 AND RESPSex = 0.
+EXECUTE.
+
+VARIABLE LABELS
+G5 "Women reporting being the decision maker in decision-making entities".
+VARIABLE LABELS
+i "Number of women who confirm they are members of or participants in decision-making entities".
+EXECUTE.
+
+* Step 3: Count the number of cases where G5= 1 and i = 1.
+COUNT Sum_G5 = G5 (1).
+COUNT Sum_i = i(1).
+EXECUTE.
+
+* Step 4: Calculate the proportion of Sum_G5 divided by Sum_i.
+COMPUTE Proportion_Women_DM_Reports_DMakers = (Sum_G5 / Sum_i) * 100.
+VALUE LABELS Proportion_Women_DM_Reports_DMakers 0 "No meaningful participation" 100 "Meaningful Participation".
+EXECUTE.
+
+* Step 5: Display the computed results ** TAKE VALID PERCENT VALUE*.
+** to remove missing cases found when dividing by zero, use select IF first**.
+*SELECT IF (NOT MISSING(Proportion_Women_DM_Reports_DMakers )).  
+
+FREQUENCIES VARIABLES=Sum_G5 Sum_i Proportion_Women_DM_Reports_DMakers 
+  /STATISTICS=MEAN SUM
+  /ORDER=ANALYSIS.
+
+**=======================================================================================*
+***Proportion of Men in decision-making entities who report being the decision maker
+**=======================================================================================*.
+  * Step 1: Identify  men being the decision maker (G6).
+COMPUTE G6= (ENUGenEntityYN = 1 AND RGenEntityYN =1) AND RGenEntityDM=1 AND RESPSex = 1. .
+EXECUTE.
+COMPUTE j = (ENUGenEntityYN = 1 AND RGenEntityYN =1 AND RESPSex= 1). 
+EXECUTE.
+VARIABLE LABELS
+G6 "Men reporting being the decision maker in decision-making entities".
+VARIABLE LABELS
+j "Number of men who confirm they are members of or participants in decision-making entities".
+EXECUTE.
+
+* Step 3: Count the number of cases where G6= 1 and j = 1.
+COUNT Sum_G6 = G6 (1).
+COUNT Sum_j = j(1).
+EXECUTE.
+
+* Step 4: Calculate the proportion of Sum_G6 divided by Sum_j.
+COMPUTE Proportion_Men_DM_Reports_DMakers = (Sum_G6 / Sum_j) * 100.
+VALUE LABELS Proportion_Men_DM_Reports_DMakers 0 "No meaningful participation" 100 "Meaningful Participation".
+EXECUTE.
+
+* Step 5: Display the computed results ** TAKE VALID PERCENT VALUE*.
+** to remove missing cases found when dividing by zero, use select IF first**.
+*SELECT IF (NOT MISSING(Proportion_Women_DM_Reports_DMakers )).  
+
+FREQUENCIES VARIABLES=Sum_G6 Sum_j Proportion_Men_DM_Reports_DMakers 
+  /STATISTICS=MEAN SUM
+  /ORDER=ANALYSIS.
+
+
+

Indicators/gender-CC-3-4/README.md

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