Absence of disparities in anthropometric measures among Chilean indigenous and non-indigenous newborns
Bibliographic record
Abstract
BACKGROUND: Studies throughout North America and Europe have documented adverse perinatal outcomes for racial/ethnic minorities. Nonetheless, the contrast in newborn characteristics between indigenous and non-indigenous populations in Latin America has been poorly characterized. This is due to many challenges, including a lack of vital registration information on ethnicity. The objective of this study was to analyze trends in anthropometric measures at birth in Chilean indigenous (Mapuche) and non-indigenous children over a 5-year period. METHODS: We examined weight and length at birth using information available through a national data base of all birth records for the years 2000 through 2004 (n = 1,166.513). Newborns were classified ethnically according to the origins of the parents' last names. RESULT: The average birthweight was stable over the 5 year period with variations of less than 20 g in each group, and with mean values trivially higher in indigenous newborns. The proportion weighing less than 2500 g at birth increased modestly from 5.2% to 5.6% in non-indigenous newborns whereas the indigenous births remained constant at 5.2%. In multiple regression analyses, adjusting flexibly for gestational age and maternal characteristics, the occurrence of an indigenous surname added only 14 g to an average infant's birthweight while holding other factors constant. Results for length at birth were similar, and adjusted time trend variation in both outcomes was trivially small after adjustment. Anthropometric indexes at birth in Chile are quite favorable by international standards. CONCLUSION: There is only a trivial degree of ethnic disparity in these values, in contrast to conditions for ethnic minorities in other countries. Moreover, these values remained roughly constant over the 5 years of observation in this study.
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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 | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".