Mechanisms of unfamiliar face recognition in children: when and how executive functioning matters
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Unfamiliar face recognition is a critical ability that can have significant implications, such as in legal or security contexts. Despite this, little is known about the cognitive skills that support children’s ability to accurately recognise and report unfamiliar faces and how these change with age. This research examined whether executive functioning (EF), including working memory, cognitive flexibility, response inhibition, and updating, predicts school-aged children’s performance on two face recognition tasks: an old/new recognition task (Experiment 1; N = 113) and a lineup identification task (Experiment 2; N = 121). While EF was not strongly related to recognition accuracy in either task, it was associated with children’s response bias, indicating that EF supports regulation of decision thresholds rather than memory strength. Age predicted modest improvements in discriminability, but these effects were not explained by EF, indicating that other developmental factors, such as metacognition or social understanding, may also play a role. Together, these findings suggest that EF contributes more to how children regulate and apply memory decisions than to how accurately they encode or retrieve unfamiliar faces.
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.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| 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 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it