Bibliographic record
Abstract
This was an exploratory study assessing how parents talk about salient child experiences, namely injuries serious enough to require hospital ER treatment. Preschool-aged (2–5 years) and school-aged (8–13 years) children were recruited from a hospital ER, and their parents were interviewed a few days later about their children's experience. The free recall portion of interviews are assessed here. Narratives of mothers and fathers differed little, but both parents were more elaborative, i.e., more descriptive and informative, when they talked about the injury of their daughters vs. their sons. Narratives about daughters were also more cohesive and included more context-setting information, i.e., orientation to where and when events occurred. Narratives about older children were also longer, more elaborative, more cohesive, and more contextually embedded than were those about younger children. Although the amount of explicit emotion descriptors did not differ, fathers tended to emphasize the absence of an emotional reaction by their sons, but not their daughters. Results were discussed in terms of concordance with gender stereotypes that describe males as tough and females as fragile. (Narratives, Gender, Parents, Story-telling)
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.
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 | 0.004 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.001 | 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 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".