The practice of historical ecology: What, when, where, how and what for
Bibliographic record
Abstract
In recent decades, there has been a growing number of studies exploring the historical dimensions of the interconnectedness of human societies and the environment. A core approach in this field is historical ecology. We analyzed 544 historical-ecological papers to assess patterns and trends in the field. We found a high degree of interdisciplinarity with a focus on local case studies, of periods of fewer than 500 years, analyzing archival sources through quantitative approaches. The proportion of papers containing management recommendations has increased over time. To make historical ecology globally relevant, more effort should be made to utilize studies across languages, borders and worldviews. We call for high standards regarding the use of social scientific methodologies. Lastly, we argue that fostering longer-term studies and assessing the real-life impact of policy recommendations emerging from historical ecology can help the discipline better contribute solutions to the challenges facing humanity in an uncertain future.
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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 | 0.007 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.008 |
| Science and technology studies | 0.001 | 0.006 |
| Scholarly communication | 0.006 | 0.007 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.004 | 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".