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Record W2911925690 · doi:10.5539/jsd.v12n1p108

The Mediterranean Way a model to achieve the 2030 Agenda Sustainable Development Goals (SDGs)

2019· article· en· W2911925690 on OpenAlexvenueno aff
Elvira Tarsitano, Gabriella Calvano, Elisabetta Cavalcanti

Bibliographic record

VenueJournal of Sustainable Development · 2019
Typearticle
Languageen
FieldEnvironmental Science
TopicAgriculture Sustainability and Environmental Impact
Canadian institutionsnot available
Fundersnot available
KeywordsMediterranean dietMediterranean climateMediterranean BasinSustainable developmentMediterranean seaGeographyBiodiversityConsumption (sociology)Environmental resource managementEnvironmental protectionEnvironmental planningEcologySociologyBiologyEconomicsSocial science

Abstract

fetched live from OpenAlex

The Mediterranean diet, inscribed in the representative list of the intangible cultural heritage of humanity by UNESCO in 2010, is inspired by the traditional food models of Italy, France, Greece, Spain, Portugal, Morocco, Cyprus and Croatia, all countries bordering the Mediterranean Sea. In particular, the Mediterranean area, geographically and territorially, has the characteristics to give value to past food models, which are products of the local territory (legumes, grains, vegetables, fruit, fish). The major aim is to encourage this type of food, which has always been one of the key points for biology studies in the fields of nutrition, food safety and biodiversity protection. The notion of "Mediterranean diet", or "Mediterranean way. How to eat well and stay well” (Keys & Keys, 1975) does not refer only to a nutritional model shared by many peoples of the Mediterranean basin, but embraces wider and deeper concepts that refer to a peculiar lifestyle, to a specific modality of production and consumption of food, to a certain way of conceiving the relationship between people and the environment. The Mediterranean way is a tool for achieving the goals of the 2030 Agenda for Sustainable Development

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 distilled prediction

Teacher imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.494
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0040.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0020.000
Scholarly communication0.0000.001
Open science0.0020.001
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0010.000

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.

Opus teacher head0.011
GPT teacher head0.227
Teacher spread0.216 · 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 teacher head, not a consensus.

Study designNot applicable
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".

Quick stats

Citations19
Published2019
Admission routes1
Has abstractyes

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