From Mythological Ages to Anthropocene: Nature and Human Relationship
Bibliographic record
Abstract
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.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.005 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.006 | 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".