321 Transaction Structures and Natural Organizations of Apprenticeship in Authentic Science Laboratories
Bibliographic record
Abstract
Educators and researchers have encouraged students ’ experiences of authentic science and their participation in activities in the science workplace. But little research has investigated the transactions between scientist/technicians and newcomers (high school students) to scientific settings. Without a pedagogical background or experience in teaching high school students, this study examines how scientists/technicians interact with students and how students interact with non-teachers in real scientific laboratories. Drawing on conversation analysis, we analyze the minute-by-minute transactions to investigate participation trajectories, transaction structures, and transaction organizations of apprenticeship in scientific laboratories. Through individual and collective analysis, our study found that demonstration-practice-connect (DPC) phases constantly recur in the process of “doing ” science; initiate-clarify-reply (ICR) and initiate-reply-clarify-reply (IRCR) frequently happen in conversational transactions; preference organization is composed not only of preferred and dispreferred modes of responding but also personally dispreferred modes; the formulating organization not only includes self-formulating but formulating others. These
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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 | 0.005 | 0.018 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.004 | 0.009 |
| Scholarly communication | 0.007 | 0.006 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".