Stories from Globalgiving Storytelling Project

Search Again Compare Tutorial Learn more Story View

6 stories matched Female and Under 16 and Respect and member and food

Your search did not match enough stories to do a complete analysis. Only basic information is showing.

How good is this collection? (41/100)
When making inferences, it is important to have many perspectives. Running our story quality test will measure this using the diversity of story collectors, named organizations, locations, and the balance in story point of view and tone to estimate the collection's suitability for meta-analysis.
Each component of the score is between 0 and 100, with 100 being the best and 0 being the worst.

Diverse sources: 3/100 (highest when collection contains hundreds of stories with miniminal overlap among the storytellers, named organizations, and locations)
Completeness: 97/100 (100% when every storytellers answer every question)
Diverse points of view: 0/100 (100% when there is a good balance of points of view. Personal experiences carry more weight over organization perspectrives.
Balance in story tone: 64/100 (100% if collection has a balance of positive and negative perspectives)
Your collection has a negative tone.

q2:One day as I walked around our village, I saw a man who asked me if i knew anything about a person who was poor and needy. No minite to spare, my .mind took me back to a beggar who once begged me for food. He was poor, had no where to live and nothing to eat. His name was Sanya. In a spur of a moment, he passed there and i introduced him to the man. Sanya was sponsored and taken back to school. After the socandary school he started a business os fish-selling while in part time school in one of the colleges around. Later, he was employed as a security guard in one company. Late two thousand and ten, the company promoted him and he became the company secretary. The company manager died of cancer and Sanya became the manager. He got married and were blesses with two children. Sanya is now in Asia working as an electrical engineer. He has a company in Nairobi and has built a big house. People are now planning to elect him as their member of parliament this year.
Q3:Sanya the wealthy man
Q4:individual
Q6:Kenya
Q7:Machakos
Q8:Ngelani
Q9:7-12 months ago
Q10:Female
Q12:Helped make it happen
Q13:The right people
Q15:Yes
Q17:[HORIZON]Question 00 was not answered <<08-03-2012-MACHAKOS-s#011-p#01>> _
Q18:Inspired
Q19:Food and shelter,Knowledge,Respect
Q23:99
Q37:Good idea that succeeded
Q38:Specific solution
Q39:Physical well-being
Q40:Lasting change
Q122:Under 16
Q132:-1.41667000000000
Q133:37.23333000000000
Q134:Individual

q2:Members of Redcross donated food stuff and blankets to the drought hit areas this has beneft member society.more to that it offered scholarships to the youths of that area that had passed in their final exams and had not proceeded with their studies due to financial instability.
Q3:donation
Q4:Redcross community
Q6:KENYA
Q7:NAIROBI
Q8:Kasarani
Q9:2-6 months ago
Q10:Female
Q12:Saw it happen
Q13:The wrong people
Q15:Yes
Q17:<<2011-05-31-NGONG&UTHIRU-S#-229P#01>>_
Q18:Important
Q19:Security,Respect,Freedom
Q23:-1
Q37:Good idea that succeeded
Q38:Specific problem
Q39:Physical well-being
Q40:Lasting change
Q122:Under 16

q2:Members of Redcross community donated food stuff and blankets to the drought hit areas this has benefit member society.More to that it offered scholarships to the youths of that area that had passed in their final exams and had not proceeded with their studies due to financial instability.
Q3:Donation
Q4:Red cross community
Q6:KENYA
Q7:NAIROBI
Q8:Kasarani
Q9:2-6 months ago
Q10:Female
Q12:Saw it happen
Q13:The right people
Q15:Yes
Q17:<<2011-05-31-NGONG&UTHIRU-S#-229P#01>>_
Q18:Important
Q19:Security,Respect,Freedom
Q23:-1
Q37:Good idea that succeeded
Q38:Specific problem
Q39:Physical well-being
Q40:Lasting change
Q122:Under 16

q2:Members of redcross community donate foodstuffs and blankets to the drought hit area,this has benefited members of society .In Kiambu for instance there were flooding in the nearby area as a pipe which was passing water bursted along the roads and started flowing down hills carrying peoples houses.
Q3:DONATION
Q4:INDIVIDUAL
Q5:flooding, hit, houses, society, members
Q6:KENYA
Q7:NAIROBI
Q8:KIAMBU
Q9:2-6 months ago
Q10:Female
Q12:Saw it happen
Q13:The right people
Q15:No
Q17:DELPHINE OBWITIKHE <<2011-05-31-NGONG&UTHIRU-S#058-P#01>> _
Q18:Important
Q19:Security,Respect,Freedom
Q23:-1
Q37:Good idea that succeeded
Q38:Specific problem
Q39:Social relations
Q40:Lasting change
Q122:Under 16
Q132:-1.13333000000000
Q133:34.55000000000000
Q134:Individual

q2:Member of redcross community donated food stuff and blanket to the drought hit area ,this has beffited members of society.They also created a church for the residents and even told them that they should started schooling also in the church when the school is under construction.
Q3:DONATION
Q4:INDVIDUAL
Q6:KENYA
Q7:NAIROBI
Q8:UTHIRU
Q9:1-2 years ago
Q10:Female
Q12:Was affected by what happened
Q13:The right people
Q15:No
Q17:RUTH NJAMBI<<2011-05-31-NGONG&UTHIRU-S#052-P#01>>_
Q18:Important
Q19:Security,Respect,Freedom
Q23:-1
Q37:Good idea that succeeded
Q38:Specific problem
Q39:Physical well-being
Q40:Lasting change
Q122:Under 16
Q132:-1.25000000000000
Q133:36.71667000000000
Q134:Individuals

q2:Members of Redcross Community donated foodstuffs and blankets to the drought hit. Area this has benefit members of society. especially the ones from Kitui since the foodstuffs gave them energy and ability hence they came up with an Idea of starting an Irrigation scheme In their areathat was aLmost fuLLy financed by the Redcross.
Q3:DONATION
Q4:RED CROSS COMMUNITY
Q5:irrigation, starting, ability, especially, idea
Q6:KENYA
Q7:MOMBASA
Q8:KILIFI
Q9:1-2 years ago
Q10:Female
Q12:Was affected by what happened
Q13:The right people
Q15:Yes
Q17:<<2011-05-31-NGONG & UTHIRU-S#228-P#01>>_
Q18:Important
Q19:Physical Needs,Respect,Freedom
Q23:-1
Q37:Good idea that succeeded
Q38:Broad need
Q39:Social relations
Q40:Lasting change
Q122:Under 16
Q132:-4.05052000000000
Q133:39.66490000000000
Q134:Red Cross

Found 6 records.
mysql icon_filters: group_id between 0 and 5000 and q10 = 'Female' and q19 like '%Respect%' and q122 = 'Under 16' and (( q2 like '%member%' and q2 like '%food%' ) or ( q3 like '%member%' and q3 like '%food%' ) or ( q4 like '%member%' and q4 like '%food%' ) or ( q5 like '%member%' and q5 like '%food%' ) or ( q6 like '%member%' and q6 like '%food%' ) or ( q7 like '%member%' and q7 like '%food%' ) or ( q8 like '%member%' and q8 like '%food%' ) or ( q11 like '%member%' and q11 like '%food%' ) or ( q17 like '%member%' and q17 like '%food%' ) or ( q26 like '%member%' and q26 like '%food%' ) or ( q27 like '%member%' and q27 like '%food%' ) or ( q28 like '%member%' and q28 like '%food%' ) or ( q29 like '%member%' and q29 like '%food%' ) or ( q35 like '%member%' and q35 like '%food%' ) or ( q41 like '%member%' and q41 like '%food%' ) or ( q42 like '%member%' and q42 like '%food%' ) or ( q43 like '%member%' and q43 like '%food%' ) or ( q46 like '%member%' and q46 like '%food%' ) or ( q47 like '%member%' and q47 like '%food%' ) or ( q60 like '%member%' and q60 like '%food%' ) or ( q65 like '%member%' and q65 like '%food%' ) or ( q70 like '%member%' and q70 like '%food%' ) or ( q71 like '%member%' and q71 like '%food%' ) or ( q72 like '%member%' and q72 like '%food%' ) or ( q73 like '%member%' and q73 like '%food%' ) or ( q74 like '%member%' and q74 like '%food%' ) or ( q75 like '%member%' and q75 like '%food%' ) or ( q76 like '%member%' and q76 like '%food%' ) or ( q77 like '%member%' and q77 like '%food%' ) or ( q80 like '%member%' and q80 like '%food%' ) or ( q81 like '%member%' and q81 like '%food%' ) or ( q86 like '%member%' and q86 like '%food%' ) or ( q87 like '%member%' and q87 like '%food%' ) or ( q88 like '%member%' and q88 like '%food%' ) or ( q89 like '%member%' and q89 like '%food%' ) or ( q98 like '%member%' and q98 like '%food%' ) or ( q99 like '%member%' and q99 like '%food%' ) or ( q110 like '%member%' and q110 like '%food%' ) or ( q111 like '%member%' and q111 like '%food%' ) or ( q116 like '%member%' and q116 like '%food%' ) or ( q117 like '%member%' and q117 like '%food%' ) or ( q123 like '%member%' and q123 like '%food%' ) or ( q125 like '%member%' and q125 like '%food%' ) or ( q132 like '%member%' and q132 like '%food%' ) or ( q133 like '%member%' and q133 like '%food%' ) or ( q134 like '%member%' and q134 like '%food%' ) or ( q135 like '%member%' and q135 like '%food%' ) or ( q136 like '%member%' and q136 like '%food%' ) or ( q138 like '%member%' and q138 like '%food%' ) or ( q141 like '%member%' and q141 like '%food%' ) or ( q142 like '%member%' and q142 like '%food%' ) or ( q151 like '%member%' and q151 like '%food%' )) LIMIT 4000;
filter_questions ['q10', 'q19', 'q122']
merge:ignore
A[Ng8MfvFsw1pU]:SUCCESS: 1 rows inserted.
not enough values to unpack (expected 3, got 2)