Stories from Globalgiving Storytelling Project

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1 stories matched Female and Under 16 and Food and shelter and business and loan and woman

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How good is this collection? (58/100)
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: 1/100 (highest when collection contains hundreds of stories with miniminal overlap among the storytellers, named organizations, and locations)
Completeness: 93/100 (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: 76/100 (100% if collection has a balance of positive and negative perspectives)
Your collection has a negative tone.

q2:An organisation calle "improve life" offer money for the small business oriented people. The money is given in form of a loan and repaid back with a certain fee. One can borrow as little as Kshs.5000.00 and pay back within a certain period. This has really helped a woman who had been thrown out by her husband. Mary borrowed Kshs.100 from a friend and put up a small structure for selling vegetables and fruits to take care of her two children. Through the help of this organisation her business has expanded tremendously to an extend that her husband came back begging for forgiveness.
Q3:Suffered rejection
Q4:Improve life
Q6:KENYA
Q7:NAIROBI
Q8:Soweto
Q9:More than 2 years ago
Q10:Female
Q12:Was affected by what happened
Q13:The right people
Q15:Yes
Q17:[HORIZON]Q19PHONE NUMBER MISSING<<22-01-2012-SOWETO-S#001-P#018>>_n/a
Q18:Inspired
Q19:Food and shelter,Family and Friends,Self-esteem
Q23:28
Q37:Good idea that succeeded
Q38:Mixed
Q39:Mixed
Q40:It requires a continuous effort
Q122:Under 16
Q132:-1.31487200000000
Q133:36.80095900000000
Q134:None

Found 1 records.
mysql icon_filters: group_id between 0 and 5000 and q10 = 'Female' and q19 like '%Food and shelter%' and q122 = 'Under 16' and (( q2 like '%business%' and q2 like '%loan%' and q2 like '%woman%' ) or ( q3 like '%business%' and q3 like '%loan%' and q3 like '%woman%' ) or ( q4 like '%business%' and q4 like '%loan%' and q4 like '%woman%' ) or ( q5 like '%business%' and q5 like '%loan%' and q5 like '%woman%' ) or ( q6 like '%business%' and q6 like '%loan%' and q6 like '%woman%' ) or ( q7 like '%business%' and q7 like '%loan%' and q7 like '%woman%' ) or ( q8 like '%business%' and q8 like '%loan%' and q8 like '%woman%' ) or ( q11 like '%business%' and q11 like '%loan%' and q11 like '%woman%' ) or ( q17 like '%business%' and q17 like '%loan%' and q17 like '%woman%' ) or ( q26 like '%business%' and q26 like '%loan%' and q26 like '%woman%' ) or ( q27 like '%business%' and q27 like '%loan%' and q27 like '%woman%' ) or ( q28 like '%business%' and q28 like '%loan%' and q28 like '%woman%' ) or ( q29 like '%business%' and q29 like '%loan%' and q29 like '%woman%' ) or ( q35 like '%business%' and q35 like '%loan%' and q35 like '%woman%' ) or ( q41 like '%business%' and q41 like '%loan%' and q41 like '%woman%' ) or ( q42 like '%business%' and q42 like '%loan%' and q42 like '%woman%' ) or ( q43 like '%business%' and q43 like '%loan%' and q43 like '%woman%' ) or ( q46 like '%business%' and q46 like '%loan%' and q46 like '%woman%' ) or ( q47 like '%business%' and q47 like '%loan%' and q47 like '%woman%' ) or ( q60 like '%business%' and q60 like '%loan%' and q60 like '%woman%' ) or ( q65 like '%business%' and q65 like '%loan%' and q65 like '%woman%' ) or ( q70 like '%business%' and q70 like '%loan%' and q70 like '%woman%' ) or ( q71 like '%business%' and q71 like '%loan%' and q71 like '%woman%' ) or ( q72 like '%business%' and q72 like '%loan%' and q72 like '%woman%' ) or ( q73 like '%business%' and q73 like '%loan%' and q73 like '%woman%' ) or ( q74 like '%business%' and q74 like '%loan%' and q74 like '%woman%' ) or ( q75 like '%business%' and q75 like '%loan%' and q75 like '%woman%' ) or ( q76 like '%business%' and q76 like '%loan%' and q76 like '%woman%' ) or ( q77 like '%business%' and q77 like '%loan%' and q77 like '%woman%' ) or ( q80 like '%business%' and q80 like '%loan%' and q80 like '%woman%' ) or ( q81 like '%business%' and q81 like '%loan%' and q81 like '%woman%' ) or ( q86 like '%business%' and q86 like '%loan%' and q86 like '%woman%' ) or ( q87 like '%business%' and q87 like '%loan%' and q87 like '%woman%' ) or ( q88 like '%business%' and q88 like '%loan%' and q88 like '%woman%' ) or ( q89 like '%business%' and q89 like '%loan%' and q89 like '%woman%' ) or ( q98 like '%business%' and q98 like '%loan%' and q98 like '%woman%' ) or ( q99 like '%business%' and q99 like '%loan%' and q99 like '%woman%' ) or ( q110 like '%business%' and q110 like '%loan%' and q110 like '%woman%' ) or ( q111 like '%business%' and q111 like '%loan%' and q111 like '%woman%' ) or ( q116 like '%business%' and q116 like '%loan%' and q116 like '%woman%' ) or ( q117 like '%business%' and q117 like '%loan%' and q117 like '%woman%' ) or ( q123 like '%business%' and q123 like '%loan%' and q123 like '%woman%' ) or ( q125 like '%business%' and q125 like '%loan%' and q125 like '%woman%' ) or ( q132 like '%business%' and q132 like '%loan%' and q132 like '%woman%' ) or ( q133 like '%business%' and q133 like '%loan%' and q133 like '%woman%' ) or ( q134 like '%business%' and q134 like '%loan%' and q134 like '%woman%' ) or ( q135 like '%business%' and q135 like '%loan%' and q135 like '%woman%' ) or ( q136 like '%business%' and q136 like '%loan%' and q136 like '%woman%' ) or ( q138 like '%business%' and q138 like '%loan%' and q138 like '%woman%' ) or ( q141 like '%business%' and q141 like '%loan%' and q141 like '%woman%' ) or ( q142 like '%business%' and q142 like '%loan%' and q142 like '%woman%' ) or ( q151 like '%business%' and q151 like '%loan%' and q151 like '%woman%' )) LIMIT 4000;
filter_questions ['q10', 'q19', 'q122']
merge:ignore
A[WPU6VkbR9hqW]:SUCCESS: 1 rows inserted.
not enough values to unpack (expected 3, got 2)