Visuospatial Attention and Discrimination of Oriented Gabor Patches in Children as a Function of Birth Experience
Bibliographic record
Abstract
Introduction: Recent studies have shown that visuospatial attentional performance in 3-month-olds is influenced by their birth experience, that is, whether they were delivered via C-section or vaginally. That is, infants delivered by C-section allocated attention and eye movements slower than infants delivered vaginally. What is not known, however, is whether birth experience persists to affect attentional performance as children age. Method: Seven- to 8- and 9- to 10-year-old participants’ visuospatial attention as a function of their birth mode was, therefore, assessed in a perceptual detection task in which they needed to indicate whether a tilted Gabor patch had been presented. Prior to presentation of the target Gabor patch, either a cue or no cue was briefly presented at the patch location to assess the impact of attention due to birth mode. Children indicated with a button press across 60 trials whether a tilted Gabor patch had been presented. Results: Analyses indicated that the 7- to 8-year-olds, delivered by C-section, exhibited lower accuracy in both cue and no-cue conditions relative to those delivered vaginally and to all 9- to 10-year-olds. Reaction time differences (no-cue mean RT – cue mean RT per participant) were calculated to standardize the measure across participants. Seven- to 8-year-olds delivered via C-section had greater reaction time differences than those delivered vaginally, and the 9- to 10-year-olds delivered via C-section. Conclusion: These findings suggest that consistent with previous findings with infants, C-section birth’s impact on attention persists into childhood, perhaps via a speed-accuracy tradeoff. This impact, however, might wane, or perhaps be modulated by other developing processing mechanisms, as they get older.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 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 | 0.001 |
| 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".