A network approach reveals surprises about the history of the niche
Bibliographic record
Abstract
Abstract The ecological niche is a prominent theoretical concept in many ecological fields, central to ecological understanding of species interactions and community structure. To better understand this important concept, and the impact it has had on ecology, we used a citation analysis to examine the history of the niche through citation patterns during the 20th century. In particular, we sought to document the spread of the niche across ecological subdisciplines, to evaluate whether the existence of different niche definitions facilitated the spread of the niche, and to see whether the conceptual integration stemming from adoption of the niche has also yielded an integration of the niche literature across subdisciplinary boundaries. We show that the ecological niche has been adopted by a number of subdisciplines, but that this success does not appear to have relied strongly on the different niche definitions, nor has it led to general integration of the niche literature across subdisciplinary boundaries. Our analysis thus not only examines the history of one of ecology's central concepts but also suggests that despite the conceptual unification that resulted from the broad adoption of the niche, a unified niche literature had not emerged by the close of the 20th century.
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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 | 0.004 | 0.023 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.009 | 0.010 |
| Science and technology studies | 0.002 | 0.005 |
| Scholarly communication | 0.006 | 0.011 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.006 | 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".