Stories from Globalgiving Storytelling Project

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2 stories matched Fun and Female and (31-45 or 46-60 or Over 60) and member and food

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How good is this collection? (61/100)
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Each component of the score is between 0 and 100, with 100 being the best and 0 being the worst.

Diverse sources: 2/100 (highest when collection contains hundreds of stories with miniminal overlap among the storytellers, named organizations, and locations)
Completeness: 94/100 (100% when every storytellers answer every question)
Diverse points of view: 60/100 (100% when there is a good balance of points of view. Personal experiences carry more weight over organization perspectrives.
Balance in story tone: 89/100 (100% if collection has a balance of positive and negative perspectives)
Your collection has a negative tone.

q2:Prison life can be traumatizing especially for women and mothers whose children are brought up within this environment. The social stigma associated with imprisonment makes it difficult for them to be accepted, no encouragement and hope from family and friends once they are out of jail. But thankfully, some organisations are waking up to this challenge and offering help to these 'ignored' members of our society Example is Judith Akinyi who was introduced by a friend to Life Bridge Foundation after suffering rejection from her relatives. Her most urgent need s to be re-united with her children whom she longs to see them and is also planning to start a food kiosk or a clothes selling business once she gets the cash she's waiting for from this organisation as a loan.
Q3:Life after prison
Q4:Life Bridge Foundation
Q6:Kenya
Q7:Nairobi
Q8:Kayole
Q9:2-6 months ago
Q10:Female
Q12:Saw it happen
Q13:The right people
Q15:Yes
Q17:<<2012-12-2-SIAYA-S#90-P#01>>_
Q18:Happy
Q19:Knowledge,Self-esteem,Fun
Q23:50
Q37:Good idea that worked somewhat
Q38:Mixed
Q39:Mixed
Q40:It requires a continuous effort
Q122:31-45
Q132:None
Q133:None
Q134:UNITED NATIONS

q2:Nalongo lilian narrated that that her husband died three years back and l;eft nothing like a job where income can be got to run the family.She engaged in looking for people's garden to dig (ekibakasi) to get food for family members but she reached a time and totally get defeated with school dues for offspring-however, she greately appreciated kakaile alex-a neighbour who promised to raise school requirement to some of her children and up to know,they are at school because of his efforts.She is allso able to attend to other needs with no pressure.
Q3:Family support(school fees for children)
Q4:Individual
Q5:engaged, raise, job, needs, income
Q6:uganda
Q7:jinja
Q8:kitovu kisenyi
Q9:1-2 years ago
Q10:Female
Q12:Saw it happen
Q13:The right people
Q15:Yes
Q17: <<2011-07-12-ORG-KACHEERA SACCO-S#353-P#01>>_
Q18:Important
Q19:Food and shelter,Knowledge,Fun
Q37:Good idea that succeeded
Q38:Specific problem
Q39:Physical well-being
Q40:Mixed
Q122:31-45
Q132:0.38333000000000
Q133:32.55000000000000
Q134:Individual

Found 2 records.
mysql icon_filters: group_id between 0 and 5000 and q10 = 'Female' and q19 like '%Fun%' and q122 in ('31-45','46-60','Over 60') 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[IIzNUJrt2j3b]:SUCCESS: 1 rows inserted.
not enough values to unpack (expected 3, got 2)