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    Home / Central Data Catalog / UGA_2017_ILGUIE_V01_M / variable [F26]
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Impact Evaluation of the Improvement of Land Governance to Increase Productivity of Small-Scale Farmers on Mailo-Land 2017

Uganda, 2017 - 2018
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Reference ID
UGA_2017_ILGUIE_v01_M
Producer(s)
Daniel Ali Ayalew, Klaus Deininger, Thea Hilhorst
Metadata
DDI/XML JSON
Created on
Mar 22, 2021
Last modified
Mar 22, 2021
Page views
46804
  • Study Description
  • Data Dictionary
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  • Data files
  • ASEC1.dta
  • ASEC2A.dta
  • ASEC2B.dta
  • ASEC3A.dta
  • ASEC3A_33.dta
  • ASEC3A_33_a.dta
  • ASEC3B.dta
  • ASEC4A.dta
  • ASEC4A_1.dta
  • ASEC5A.dta
  • ASEC5A_1.dta
  • ASEC5B.dta
  • ASEC6A.dta
  • ASEC6B.dta
  • ASEC6C.dta
  • ASEC7A.dta
  • ASEC7B.dta
  • ASEC8.dta
  • ASEC9.dta
  • ASEC9_Ext.dta
  • ASEC10.dta
  • ASEC11.dta
  • GSEC1.dta
  • GSEC2.dta
  • GSEC3.dta
  • GSEC4.dta
  • GSEC5.dta
  • GSEC6.dta
  • GSEC7a.dta
  • GSEC7b.dta
  • GSEC8.dta
  • GSEC9a.dta
  • GSEC9b.dta
  • GSEC10.dta
  • GSEC11.dta
  • GSEC12.dta
  • GSEC13a.dta
  • GSEC13b.dta
  • GSEC13c.dta
  • GSEC13d.dta
  • GSEC13e_Male.dta
  • GSEC13f_female.dta
  • GSEC14.dta

SubCategory Level1 - ISCO code (B2_twoDigit)

Data file: GSEC4.dta

Overview

Valid: 650
Invalid: 7505
Minimum: 11
Maximum: 993
Type: Discrete
Decimal: 2
Start: 204
End: 209
Width: 6
Range: 11 - 993
Format: Numeric

Questions and instructions

Question pretext
Using this information, code the activity using the main category and subcategory levels1 to level3 ISCO codes that follow
Categories
Value Category Cases
11 Chief executives, senior officials and legislators 2
0.3%
12 Administrative and commercial managers 1
0.2%
13 Production and specialized services managers 4
0.6%
14 Hospitality, retail and other services managers 1
0.2%
21 Science and engineering professionals 0
0%
22 Health professionals 9
1.4%
23 Teaching professionals 77
11.8%
24 Business and administration professionals 4
0.6%
25 Information and communications technology professionals 0
0%
26 Legal, social and cultural professionals 1
0.2%
31 Science and engineering associate professionals 3
0.5%
32 Health associate professionals 1
0.2%
33 Business and administration associate professionals 2
0.3%
34 Legal, social, cultural and related associate professionals 1
0.2%
35 Information and communications technicians 0
0%
41 General and keyboard clerks 0
0%
42 Customer services clerks 0
0%
43 Numerical and material recording clerks 1
0.2%
44 Other clerical support workers 3
0.5%
51 Personal service workers 44
6.8%
52 Sales workers 18
2.8%
53 Personal care workers 0
0%
54 Protective services workers 4
0.6%
61 Market-oriented skilled agricultural workers 7
1.1%
62 Market-oriented skilled forestry, fishery and hunting workers 2
0.3%
63 Subsistence farmers, fishers, hunters and gatherers 14
2.2%
71 Building and related trades workers, excluding electricians 18
2.8%
72 Metal, machinery and related trades workers 4
0.6%
73 Handicraft and printing workers 4
0.6%
74 Electrical and electronic trades workers 0
0%
75 Food processing, wood working, garment and other craft and related trades workers 3
0.5%
81 Stationary plant and machine operators 0
0%
82 Assemblers 0
0%
83 Drivers and mobile plant operators 21
3.2%
91 Cleaners and helpers 17
2.6%
92 Agricultural, forestry and fishery labourers 310
47.7%
93 Labourers in mining, construction, manufacturing and transport 43
6.6%
94 Food preparation assistants 8
1.2%
95 Street and related sales and service workers 10
1.5%
96 Refuse workers and other elementary workers 6
0.9%
991 Commissioned armed forces officers 1
0.2%
992 Non-commissioned armed forces officers 1
0.2%
993 Armed forces occupations, other ranks 5
0.8%
Sysmiss 7505
Warning: these figures indicate the number of cases found in the data file. They cannot be interpreted as summary statistics of the population of interest.
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