Intersecciones entre evaluación participativa y pedagogía social
Bibliographic record
Abstract
It can be argued that participatory evaluation and social pedagogy share several interconnections given their respective developments and evolutions. In this paper we explore affinities between these two domains of inquiry in order to understand points of intersection and departure at deeper levels that has occurred to date. Following a recent review and integration of more than 100 empirical studies of participatory evaluation (Cousins & Chouinard, 2012) we re-examine a selection of emergent themes through a social-pedagogical lens. We highlight similarities and differences and then lay out a set of issues for considerations for participatory evaluation and in the interest of opening an dialogue among those engaged in research and practice within either sphere if interest.
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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 | 0.123 | 0.117 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.007 | 0.007 |
| Science and technology studies | 0.005 | 0.044 |
| Scholarly communication | 0.022 | 0.020 |
| Open science | 0.003 | 0.026 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.008 | 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".