Bibliographic record
Abstract
The study of population dynamics addresses three questions that are not always separated in discussions with empirical data. Two questions address population regulation. What stabilises population density is the first question, and, in spite of much theory, little progress has been made in answering this question empirically. The assumption of an equilibrium density is impossible to test and direct experimental tests to answer this question are rare. What prevents population growth is a second question, and is the classic question of population regulation. To answer this question requires an increasing population, and, with adequate experimental manipulations, the density dependent factors preventing increase can be identified. Surprisingly, answering this question has provided little assistance in solving practical problems in population dynamics, possibly because most populations are rarely in the state of growth and show a limited range of densities. What limits population density in good and poor habitats is a third question, which addresses population limitation rather than regulation, and has been the most useful question for empirical ecologists to ask. Population limitation admits of little theory and no elegant models, and highlights the gap between theory and practice in much of ecology. Defining the question clearly and adopting an experimental approach with clear alternative hypotheses will be essential to avoiding the controversies of the past while building useful generalisations for the practical problems of population 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.
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 | 0.018 | 0.039 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.031 |
| Scholarly communication | 0.005 | 0.016 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.005 | 0.006 |
| Insufficient payload (model declined to judge) | 0.006 | 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".