<i>Beverage Consumption in</i> Low Income, “Milk-friendly’’ Families
Bibliographic record
Abstract
PURPOSE: Beverage consumption by poor, lone mother-led, "milk-friendly" families living in Atlantic Canada was characterized over a one-month income cycle. METHODS: Beverage intake and food security status were assessed weekly, using a 24-hour dietary recall and the Cornell-Radimer food insecurity questionnaire. Families were classified as "milk friendly" if total consumption of milk was 720 mL on a single day during the month. Beverage intake was assessed using t-tests, analysis of variance (ANOVA), repeated measures ANOVA with post hoc comparisons, and chi-square analysis. RESULTS: Milk consumption by milk-friendly families (76; total sample, 129) was highest at the time of the month when they had the most money to spend. During all time intervals, mothers consumed the least amount of milk and children aged one to three years consumed the most. Mothers consumed carbonated beverages disproportionately, while children of all ages consumed more fruit juice/drink. Mothers' coffee consumption was profoundly increased when either they or their children were hungry. CONCLUSIONS: The quality of beverage intake by members of low-income households fluctuates in accordance with financial resources available to purchase foods. Mothers' beverage intake is compromised by the degree of food insecurity the family experiences.
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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 | 0.001 | 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) | 0.001 | 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 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".