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Record W2801275216 · doi:10.5539/ies.v11n5p94

From Mythological Ages to Anthropocene: Nature and Human Relationship

2018· article· en· W2801275216 on OpenAlexvenueno aff
Halide Gamze İnce Yakar

Bibliographic record

VenueInternational Education Studies · 2018
Typearticle
Languageen
FieldArts and Humanities
TopicCultural and Sociopolitical Studies
Canadian institutionsnot available
Fundersnot available
KeywordsMythologyHumanityEnvironmental ethicsSociologyIntellectEcologyEcological crisisAnthropoceneHolismEpistemologyHistoryPhilosophyLawPolitical science

Abstract

fetched live from OpenAlex

Ecological problems are some of the most important items on the agenda of humanity in the 21st century. Adding spiritual depth, ethical point of view and basic human traditions to the contribution that human beings provide to ecological problems through intellect will provide realistic and lasting results. In the Palaeolithic Age, where man is under the domination of nature, he owes gratitude to the divine power of nature and worships its elements. With the beginning of industrialization, myths were only old-time stories for humanity. Due to the holism rule of ecology the salvation of nature may be possible by all the living things in the ecosystem behaving in the same way and with the same interaction. Today, there is a need for nature education in which we can teach all mankind that protecting a tree is no different from protecting a forest. Myths in the world we live today remind us of the spiritual, inner richness that nature provides to man; is an effective educational material in the sense that their ancestors can repeat their life integrated with nature. Mythology should be included in nature education. For a qualified nature education, we need the magical atmosphere that mythological stories will create. In addition to this, Duha Kocaoglu Deli Dumrul Epic will examine the historical ecological perspective of the Turkish community and the messages they give to solve their present ecological problems.

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)0.000
metaresearch head score (Gemma)0.001
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.686
Threshold uncertainty score0.951

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.001
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0000.000
Research integrity0.0000.000
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 head0.153
GPT teacher head0.440
Teacher spread0.287 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
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

Citations1
Published2018
Admission routes1
Has abstractyes

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