Mutual Contributions of Individuals, Partners, and Institutions: Planning to Remember in Girl Scout Cookie Sales
Bibliographic record
Abstract
Abstract This paper argues that planning entails distributed, mutual contributions of individuals, their social partners, and their community institutions. We suggest that these mutually involved contributions can be viewed through shifts in focus of analysis, contrasting with analyses of cognitive development that treat individuals as though they exist apart from their social and cultural worlds. We illustrate this argument with a study examining the distributed nature of planning to remember in a complex everyday task. We investigated the personal, interpersonal, and institutional cognitive contributions of 16 Girl Scouts, their mothers and customers and other companions, and institutions (the national organization and the cookie company) in keeping track of deliveries and planning collection of money in Girl Scout cookie sales and deliveries. The article also discusses an analytic methodology (Functional Pattern Analysis) for abstracting findings from the details of rich ethnographic data. Individual scouts, their mothers, customers, and the scouting organization and cookie company all played significant roles in keeping track of progress. In particular, tools and supports provided by the cookie company played a key role in organizing the cognitive tasks, and the scouts collaborated in planning with other people (usually their mothers and customers). Our findings illustrate the importance of examining contributions beyond those of the individual, while still recognizing the active roles of individuals in thinking. We argue that conceiving of individual, interpersonal, and institutional/cultural contributions as mutually constituting aspects of cognitive activities supports this aim beyond the usual focus on separate individual and ‘external’ factors.
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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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.004 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".