Binding an event to its source at encoding improves children’s source monitoring.
Bibliographic record
Abstract
Children learn information from a variety of sources and often remember the content but forget the source. Whereas the majority of research has focused on retrieval mechanisms for such difficulties, the present investigation examines whether the way in which sources are encoded influences future source monitoring. In Study 1, 86 children aged 3 to 8 years participated in 2 photography sessions on different days. Children were randomly assigned to either the Difference condition (they were asked to pay attention to differences between the 2 events), the Memory control condition (asked to pay attention with no reference to differences), or the No-Instruction control (no special instructions were given). One week later, during a structured interview about the photography session, the 3- to 4-year-olds in the No-Instruction condition were less accurate and responded more often with 'do not know' than the 7- to 8-year-olds. However, the older children in the Difference condition made more source confusions than the younger children suggesting improved memory for content but not source. In Study 2, the Difference condition was replaced by a Difference-Tag condition where details were pointed out along with their source (i.e., tagging source to content). Ninety-four children aged 3 to 8 years participated. Children in the Difference-Tag condition made fewer source-monitoring errors than children in the Control condition. The results of these 2 studies together suggest that binding processes at encoding can lead to better source discrimination of experienced events at retrieval and may underlie the rapid development of source monitoring in this age range. (PsycINFO Database Record
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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 | 0.006 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| 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".