The impact of information and communication technology on the technical efficiency of smallholder vegetable farms in Shandong of China
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Abstract Farmers have started to adopt information and communication technology (ICT), which has considerable potential to impact farm performance. This study uses data from a 2018 survey of 763 vegetable smallholder farms in China to estimate the impact of ICT on technical efficiency (TE). We adopt propensity score matching to create a balanced sample of ICT users and non-users and a stochastic frontier model with sample selection correction to compare the two groups’ TE. After accounting for self-selection bias from both observables and unobservables, the study finds a positive effect of ICT use on TE. On average, the TE score of ICT users is 0.64, whereas ICT non-users have a lower score of 0.57. A quantile regression analysis further reveals a heterogeneous impact of ICT on TE, with the largest effects among less efficient farms. These results suggest that vegetable farmers’ performance could be fostered by the widespread use of ICT.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it