Bibliographic record
Abstract
Experience is suggested to shape the development of emotion processing abilities in infancy. The current dissertation investigated the influence of familiarity with particular face types and emotional faces on emotional face processing within the first year of life using a variety of metrics. The first study examined whether experience with a particular face type (own- vs. other-race faces) affected 6- and 9-month-old infants’ attentional looking preference to fearful facial expressions in a visual paired-comparison (VPC) task. Six-month-old infants showed an attentional preference for fearful over happy facial expressions when expressed by own-race faces, but not other race-faces, whereas 9-month-old infants showed an attentional preference for fearful expressions when expressed by both own-race and other-race faces, suggesting that experience influences how infants deploy their attention to different facial expressions. Using a longitudinal design, the second study examined whether exposure to emotional faces via picture book training at 3 months of age affected infants’ allocation of attention to fearful over happy facial expressions in both a VPC and ERP task at 5 months of age. In the VPC task, 3- and 5-month-olds without exposure to emotional faces demonstrated greater allocation of attention to fearful facial expressions. Differential exposure to emotional faces revealed a potential effect of training: 5-month-olds infants who experienced fearful faces showed an attenuated preference for fearful facial expressions compared to infants who experienced happy faces or no training. Three- and 5-month-old infants did not, however, show differential neural processing of happy and fearful facial expressions. The third study examined whether 5- and 7-month-old infants can match fearful and happy faces and voices in an intermodal preference task, and whether exposure to happy or fearful faces influences this ability. Neither 5- nor 7-month-old infants showed intermodal matching of happy or fearful facial expressions, regardless of exposure to emotional faces. Overall, results from this series of studies add to our understanding of how experience influences the development of emotional face processing in infancy.
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 | 0.000 | 0.001 |
| 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 | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| 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".