RESEARCH ARTICLE Open Access Gauging knowledge of developmental milestones
Bibliographic record
Abstract
Background: Parental knowledge of child development has been associated with more effective parenting strategies and better child outcomes. However, little is known about what adults who interact with children under the age of 14 years know about child development. Methods: Between September 2007 and March 2008, computer assisted telephone interviews were completed with 1443 randomly selected adults. Adults were eligible if they had interacted with a child less than 14 years of age in the past six months and lived in Alberta, Canada. Results: Sixty three percent of respondents answered two (or more) out of four questions on physical development correctly. Fifteen percent of respondents answered two (or more) out of three questions on cognitive development correctly. Seven percent of respondents answered three (or more) out of five questions on social development correctly. Two percent of respondents answered three (or more) out of five questions on emotional development correctly. Parents and females were better able to identify physical developmental milestones compared to non-parents and males. 81 % of adults correctly responded that a child’s experience in the first year of life has an important impact on later school performance, 70 % correctly responded that a child’s ability to learn is not set from birth, 50 % of adults correctly responded that children learn more from hearing someone
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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 | 0.003 | 0.020 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.000 |
| Insufficient payload (model declined to judge) | 0.039 | 0.007 |
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".