Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Whether to secure critical resource inputs or responding to demands ranging from local communities to international stakeholders, leading multinational companies increasingly engage in ecosystem management by developing operations models with biodiversity, ecosystem conservation, and ecosystem restoration in mind—often in partnership with international conservation organizations. While promising to infuse business strategy with knowledge from natural science, specifically ecology, the emerging practice appears well ahead of research in this area. This article aims to encourage research into how organizations can manage their relationship with the natural environment so as not to destroy the very life-supporting foundations provided by nature. Bridging knowledge domains, the article introduces key concepts from ecology and social ecology to organization and management studies— ecosystems, biodiversity, ecosystem services, and ecological resilience. We illustrate these concepts with advances in ecosystems management and conclude with suggestions for future research in sustainability management, organization theory, and strategic management.
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.
Full frame distilled prediction
Teacher imitationNot 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.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.013 | 0.012 |
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 it