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. 2023 Jul 12;9(7):e17520. doi: 10.1016/j.heliyon.2023.e17520

Table (A.4).

Association between GEOs and livelihood diversification (n = 260).

Livelihood diversification Nearby villages (120)
95% C. I (Near)
Distant
Villages (140)
95% C. I (Distant)
Chi-square P-value Phi
Lower bound Upper bound Lower bound Upper bound
(%) (%)
Farming 81.5 .141 .489 87.2 −.489 −.141 10.381*** .001 .200
Fishing 68.1 .068 .340 82.3 −.340 −.068 7.090*** .008 .165
Salaried employment 7.6 −.043 .349 11.3 −.349 .043 1.064 .302 .064
Investor farm wage labour 7.6 −.099 .330 8.5 −.330 .099 .078 .780 .017
Farm wage labour 9.2 .215 .502 28.4 −.502 −.215 14.970*** .000 .240
Carpentry and welding 3.4 −.081 .402 8.5 −.402 .081 2.963* .085 .107
Making bricks 3.4 .023 .468 9.9 −.468 −.023 4.320** .038 .129
Bicycle/motorbike repair 5.9 −.106 .320 9.9 −.320 .106 1.423 .233 .074
Motor-bike transport 4.2 −.179 .328 6.4 −.328 .179 .603 .438 .048
Sea-shells collection 5.0 −.116 .394 11.3 −.394 .116 3.313* .069 .113
Charcoaling 5.9 −.060 .357 9.9 −.357 .060 1.423 .233 .074
Dishwashing 5.9 −.060 .353 6.4 −.353 .060 .028 .867 .010
Mechanical and driving 3.4 −.236 .315 5.7 −.315 .236 .784 .376 .055
Housekeeping 5.0 −.100 .440 7.1 −.440 .100 .470 .493 .043
Machine Operator 3.4 −.096 .378 5.7 −.378 .096 .784 .376 .055
Boat driving 8.4 −.184 .446 21.3 −.446 .184 8.215*** .004 .178
Food vendor 5.0 .127 .443 7.8 −.443 −.127 .804 .370 .056
Petty business 6.7 −.205 .270 11.3 −.270 .205 1.647 .199 .080
Brewing local beer 3.4 −.131 .272 7.1 −.272 .131 1.763 .184 .082
Crop business 21.0 .021 .280 32.6 −.280 −.021 4.386** .036 .130
Security Guide 5.0 −.122 .327 .5 −.327 .122 .205 .272 .068

*Phi-statistics are interpreted as follows: 0 to 0.11 indicates a weak association, 0.11 to 0.30 indicates a moderate association, and 0.31 and higher indicates a significant association (Healey, 2013). Statistically significant values are indicated by the symbols *, **, and ***, respectively, at p 0.05, p 0.01 and p 0.001 respectively.