Effects of Newcomer Practicing on Cross-level Learning Distortions
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
This article fuses variance generation and suppression arguments with the micro-underpinnings of collective learning to bring the socio-emotional context of learning to the foreground. We take a practice-based perspective on cross-level learning distortions to explore non-recursive trade-offs between variance generation and variance suppression as newcomers adapt to established groups and as groups react to newcomers. Our typology first disaggregates the effects of sociality and emotionality to describe four patterns of context-contingent individual practicing: experimenting, emulating, bracketing and impersonating. We then explain why groups operating in distinct contexts may systematically ignore or discount two specific types of individual departures from collective norms: outliers (infrequent, significant deviations) and clusters (frequent, incremental changes). Our theoretical predictions add value to managers by unpacking the contextual contingencies that systematically pattern individual and collective learning and by suggesting specific interventions for preventing or alleviating learning disorders.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it