Food security and access to water in Mexican households (805.1)
Bibliographic record
Abstract
Introduction : Food security is the state in which all persons always have access to the food needed according their biological requirements, but since 2002, the FAO has mentioned that food security cannot be achieved without considering the access to water. Objective : To identify the state of food security and access to water in Mexican households. Methods: Food Security was assessed using a validated scale applied in 352 households in rural and urban communities, as well as a pilot scale to assess access to water. Results: 73 % of households were classified as food secure (level 1), 15 % as being mildly food insecure (level 2), 7% were considered food insecure at a moderate level (level 3) and only 4 % were households with severe food insecurity (level 4). At all food security levels interviewees were worried about not having enough access to water, and in the last three months 50% of households experiences water scarcity. Most of the households used tap water to prepare the milk for the children, as well as for personal hygiene. 25% of the interviews reported that water availability has declined in their households, while the cost of water has increased. Conclusions: Food security cannot be conceived without taking into account the water situation. The majority of the households report lack of access to enough water, which usually does not meet the conditions of safety for human consumption and food preparation. Grant Funding Source : None funding
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.005 | 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".