David and Goliath: comparative use of facilitation and competition studies in the plant ecology literature
Bibliographic record
Abstract
Abstract. Competition and facilitation are extensively studied in plant ecology and are central to ecological theory. However, these processes do not occur in isolation from each other and should be studied concurrently and synthetically. Here, we compare the relative citation success of studies that focus on either side of the same interaction coin in terms of number of publications and citations per publication in six of the following major themes in plant ecology: biogeography, populations, communities, ecosystems, evolution and conservation. There were eight times more publications on plant competition than on facilitation but this is not surprising given its long history of comprehensive and relatively exclusive study in plant ecology. Although studies of facilitation comprised a smaller body of literature, the mean citation rate for each publication was equivalent to that of competition studies. Thus, facilitation studies are being used as much as competition. These patterns of use by the ecological community clearly indicate that both aspects of plant interactions address broad themes and that studies on plant interactions should now strive to either test both simultaneously or at the very minimum include interpretations and relevant literature from both sets of ideas. Importantly, these broad trends illustrate the old axiom that quality and not quantity of studies may be a consideration in the success of a sub-discipline.
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 | 0.056 | 0.248 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.096 | 0.078 |
| Science and technology studies | 0.003 | 0.006 |
| Scholarly communication | 0.010 | 0.010 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".