Bibliographic record
Abstract
Because of its generally low density of humans and few settlements, the circumpolar boreal forest is often viewed as an untouched wilderness. However, archeological evidence indicates that humans have inhabited the region since the continental glaciers disappeared 8,000-12,000 years ago. This paper discusses the ecological impacts that humans have had on the boreal forest ecosystem through their activities in prehistoric, historic, and recent times and argues that the boreal forest has always been a cultural landscape with a gradient of impacts both spatially and temporally. These activities include hunting, trapping, herding, agriculture, forestry, hydroelectric dam projects, oil and natural gas development, and mining. In prehistoric times, human impacts would generally have been more temporary and spatially localized. However, the megafaunal extinctions coincident with arrival of humans were very significant ecological impacts. In historic times, the spread of Europeans and their exploitation of the boreal's natural resources as well as agricultural expansion has altered the composition and continuity of the boreal forest ecosystem in North America, Fennoscandia, and Asia. Particularly over the last century, these impacts have increased significantly (e.g., some hydroelectric dams and tar sands developments that have altered and destroyed vast areas of the boreal forest). Although the atmospheric changes and resulting climatic changes due to human activities are causing the most significant changes to the high-latitude boreal forest ecosystem, any discussion of these impacts are beyond the limits of this paper and therefore are not included.
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.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 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".