Experiencing (Pereživanie) as Developmental Category: Learning from a Fisherman who is Becoming (as) a Teacher-in-a-Village-School
Bibliographic record
Abstract
In this study, we take up L. S. Vygotsky’s challenge to study learning and development in terms of categories, irreducible units that preserve the characteristics of the whole (society). One such category (unit) is experiencing [pereživanie], a process that integrates over the relation of person and environment. Using a case study from Iceland, we theorize the process of “becoming as a teacher-in-a-village school” in terms of experiencing [pereživanie]. The case describes a stage of development in the life of a person who becomes a teacher and then experiences a developmental trajectory very different from his previous life as a fisherman. This is an aspect of teacher education that is hardly (if ever) described in the teacher education literature which tend to be concerned with events after a person has entered a professional program or after a person has begun teaching. We discuss the implications of taking experiencing [pereživanie] as the developmental unit for theory and the practice of teacher education and development.
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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 | 0.002 | 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 | 0.012 | 0.020 |
| Scholarly communication | 0.004 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.003 |
| 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".