Bibliographic record
Abstract
Prospective memory (PM) is the ability to remember to carry out one's future intentions and is a critical developmental achievement to function independently and successfully in daily life. For example, children must remember to return homework, feed their pets, and bring gifts to their friend's birthday parties. Despite children often being able to report what it was they had to do (i.e., remembering the content of their intention), forgetting to carry out one's intentions is very common in childhood. Many theoretical and methodological advances have been made in the study of children's PM over the past two decades. This chapter will describe: (1) the emergence and development of PM during the childhood years (event-based and time-based laboratory PM tasks as well as naturalistic PM tasks), (2) the role of retrospective memory and prospective/executive processes in PM development (including a description of the Executive Framework of PM development), (3) the factors that impact children's PM performance over the course of development such as motivation, cue focality, task interruption, cue salience, delay task content and length, as well as visual and verbal reminders, (4) the cognitive abilities that are closely related to or involved in PM performance (e.g., episodic foresight, planning, metacognition), and (5) how PM is affected by atypical development. I conclude by commenting on the current state of the field and highlighting important directions for future research.
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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 | 0.000 | 0.001 |
| Scholarly communication | 0.003 | 0.002 |
| 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".