Reciprocal Contributions between People and Nature: A Conceptual Intervention
Bibliographic record
Abstract
Abstract Throughout human history, Indigenous and local communities have stewarded nature. In the present article, we revisit the ancestral principle of reciprocity between people and nature and consider it as a conceptual intervention to the current notion of ecosystem services commonly used to inform sustainability transformation. We propose the concept of reciprocal contributions to encompass actions, interactions, and experiences between people and other components of nature that result in positive contributions and feedback loops that accrue to both, directly or indirectly, across different dimensions and levels. We identify reciprocal contributions and showcase examples that denote the importance of reciprocity for our ecological legacy and its relevance for biocultural continuity. We suggest that the concept of reciprocal contribution can support transformation pathways by resituating people as active components of nature and restructuring institutions so that ethical principles and practices from Indigenous and local communities can redirect policy approaches and interventions worldwide.
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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 | 0.014 | 0.010 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.008 | 0.077 |
| Scholarly communication | 0.009 | 0.011 |
| Open science | 0.002 | 0.016 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.008 | 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".