Traditional African Religion in Natural Resources Conservation and Management in Cross River State, Nigeria
Bibliographic record
Abstract
This article assessed the roles Traditional African Religion can play in the conservation and management of natural resources especially forest resources in Cross River State Nigeria. Some religious practices in the African Traditional Religion like methods worship, initiation rites, and the invocation of the sacred powers of the supreme beings, how these gods communicate their will to humans through the chief priests and how the gods are atoned if provoked were examined. The stronghold of African religion rests wholly on the ascription of psychic powers to any part of the natural environment as the abodes of the gods and goddesses of the land and the protection of these abodes of the gods/goddesses. The protection of the abodes of the gods from entrance, utilization and exploitation overtly or covertly encourages conservation and management of natural resources. Forbidden areas associated with worship contribute to natural resources conservation and management in Cross River State. These African traditional religious strategies for natural resource conservation and management have somehow been eroded by acculturation and enculturation of most African communities through the introduction of Christianity as a modern way of worship. The use of literature review and personal interviews was adopted by the authors for the study. The authors recommended a re-visitation of the principles of traditional African religious practices where modern conservation programs could integrate traditional knowledge systems into their activities in the conservation and management of our natural resources.
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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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 0.000 |
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.
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".