Mediterranean Sea of Educational Culture: Personal Narration of a Peer Learning Activity
Bibliographic record
Abstract
In this paper is describing an initiative in cultural, outdoor science education that took place in the west Crete-Greece(Chania & Rethymnon counties) in 2015, and organized in collaboration with teachers and social bodies, to connectScience, Education and Local Communities for a better quality of everyday life. The initiative concentrated inorganizing the European Educational Conference “Mediterranean Sea Connects Us: Progress in Education withLocal Communities”, which hosted as a training program that can be applied elsewhere, with different target groups,promoting the aims of participatory acquisition of knowledge by sharing them in company, with experientialactivities in moments of joy, happiness and wisdom. Educators-officials of high level and much experienced in thethree levels of Education from Greece, Cyprus, Turkey and Romania, with representatives from local bodies, wereinvited to deposit experience, aspects, ideas and expectations on future educational collaboration in the area ofBalkans, East Mediterranean and widely. As coexisting in the same geographical area, with long and importantcommon past, as collaborators in educational projects from the past, intended to be partners in important andinnovative future jointed actions in cultural STEM Education, for the progress of Mediterranean local educationalcommunities.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.007 | 0.005 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".