Bibliographic record
Abstract
Abstract This chapter documents a seismic shift that has occurred in the field of attentional development over the past decade, both in the content of the empirical data being collected and in the theoretical ideas being used to understand them. We trace the origins of this paradigm shift by first examining the past. Research during the latter half of the 20th century was dominated by the information‐processing framework, which views attention as a localizable, domain‐general, and situationally invariant cognitivefaculty,with its primary role in filtering sensory information in the service of task goals. However, during the first decade of the 2000s, researchers began to study how individual, emotional, and social aspects of life influence everyday attention behavior. Mounting evidence from these studies revealed that the classic information‐processing framework could not provide a complete account of attentional development. Thus, at present, attention is becoming viewed as a concept that cannot be isolated from social and emotional aspects of development. With regard to future directions, we outline a dynamic view of attention, in which attention is viewed as a cognitive facility, integrating the demands of “cool” cognition (i.e., the information‐processing capacities) with the “hot” functions spanning temperament, emotion, social communication, individual histories, and cultural context. If this trend continues, attentional development in the next decade will be studied as the outcome of complex interactions between an individual's biology, their life history, and their social environment.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.041 | 0.005 |
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".