Technology, rurality and gender… false friends, but not enemies!
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
Guaranteeing gender equality in the access and use of Information and Communication Technologies (ICT) has become today a determining element in the achievement of food security and as a consequence of the achievement of rural development, which constitutes one of the goals of the Food and Agriculture Organization of the United Nations (FAO). Indeed, the fight against digital gender gaps and other gaps in a general way allow a greater contribution in the agri-food sector, which is becoming increasingly digitized and technological. In fact, the objective of the study is to analyse the impact that have determined gaps, such as: force labour participation rate, literacy rate, pay rate and ICT study rate, on the participation rate gap in the agricultural sector. For this reason, a multiple linear regression is proposed that considers 64 countries and subsequently the situation of four of these countries is examined in more detail: France, Spain, Morocco and Algeria. The results of this show the existence of a positive correlation between our variables but also the effect that some socio-economic and cultural factors have on this achievement.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 | 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 | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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