Getting to Know You: Gaze Behaviours and Biographical Information in Face–Name Associations
Bibliographic record
Abstract
BACKGROUND: A person's name serves as a unique identifier, yet retrieving it is considered the most challenging aspect of person recognition. Here, we examined the role of biographical information and gaze behaviours during the acquisition and short- and long-term retrieval of face-name associations. METHODS: During Familiarization, undergraduate participants (N = 47) were presented with new face-name associations, with a biographical fact (hobby) provided for half of the pairs. During Consolidation, participants repeatedly recognized the names of the newly learned faces until they reached a criterion. Finally, Recognition of learned faces and their names was tested immediately and after delays of one and two weeks. RESULTS: Providing biographical information at learning improved both face and name recognition. Performance declined linearly as the retention interval increased, and performance at the two-week delay was superior for face-name associations learned with biographical information. This facilitation effect was accompanied by more fixations to the eyes and fewer fixations to the mouth for faces learned with biographical information. In addition, fixation counts and transitions between facial regions decreased as face-name pairs were learned and consolidated. CONCLUSION: Biographical information enhances memory for face-name associations. Increased familiarity with these associations also leads to more efficient visual processing. Together, these findings highlight functional links among nodes of the person recognition network and between memory and oculomotor processes.
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How this classification was reachedexpand
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 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".