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Record W2808089026 · doi:10.5430/wje.v8n3p65

Mediterranean Sea of Educational Culture: Personal Narration of a Peer Learning Activity

2018· article· en· W2808089026 on OpenAlexvenueno aff
Kalathaki Maria

Bibliographic record

VenueWorld Journal of Education · 2018
Typearticle
Languageen
FieldHealth Professions
TopicDigital Storytelling and Education
Canadian institutionsnot available
Fundersnot available
KeywordsCitizen journalismNarrativeSociologyHappinessPedagogyPolitical sciencePublic relations

Abstract

fetched live from OpenAlex

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.

Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.

How this classification was reachedexpand

Full frame machine prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.001
metaresearch head score (Gemma)0.005
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.007
Threshold uncertainty score0.015

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.000
Science and technology studies0.0070.005
Scholarly communication0.0030.003
Open science0.0010.005
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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.

Opus teacher head0.058
GPT teacher head0.416
Teacher spread0.357 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
Domainnot available
GenreEmpirical

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".

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Citations0
Published2018
Admission routes1
Has abstractyes

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