The Productivity‐Workload Paradox in Low‐Income Agrarian Economies: Agricultural Inputs, Mechanization, and Women's Labor Burden in Uganda

Agricultural mechanization can raise farm productivity without reducing women's agricultural labor burdens when technologies substitute for some tasks while leaving others manual. This study develops a Gendered Induced Innovation Framework to explain how agricultural support, task‐specific mechanization, and production adjustment shape women's agricultural labor burden under financial and institutional constraints. We introduce the Women's Agricultural Labor‐Burden Index (WALBI), a normalized 0–100 composite measure of the intensity, task composition, and seasonal concentration of women's agricultural work, interpreted as an operational measure of household‐level labor burden rather than physiological strain. Using nationally representative panel data from Uganda for 2005–2020 and stochastic frontier, binary logit, and semiparametric models, we examine association s between agricultural support, mechanization, productivity, and women's labor burden. The results show that these associations are task‐specific: post‐harvest mechanization is associated with lower measured burden, whereas tractor‐based mechanization shows no detectable association. Greater subsidy intensity is associated with higher productivity and greater adoption of post‐harvest and land‐preparation technologies, but also with a higher probability of high labor burden. Farm expansion is positively associated with women's burden. These findings show that productivity‐enhancing agricultural support does not necessarily reduce women's labor burdens when production expands or female‐intensive tasks remain insufficiently mechanized. Evaluating agricultural support alongside task‐specific labor outcomes can reveal gendered consequences that aggregate productivity measures overlook.