Respect for property rights: when does it pay to defend territory?
Bibliographic record
Abstract
Question: Should habitat-selecting individuals respect the property rights of territory holders or challenge them for ownership? Definitions: Ideal despotic individuals challenge others for high-quality territories and defend them against rivals. Ideal pre-emptive individuals seek only unoccupied space and surrender it when challenged by despots. Approach: Computer simulations of an evolutionary game between ideal despotic and ideal pre-emptive habitat selectors. Features of the model: Individuals of each strategy choose between two habitats. Pure strategies grow for 1000 generations after which one individual possessing the alternative strategy is allowed to invade. If the invasion fails within 10 generations, invasion is attempted again with twice as many individuals (maximum of four attempts with 1, 2, 4, and 8 individuals respectively). Each simulation is repeated 99 times. Ranges of key variables: Habitat quality: mean population growth rate = 1 vs. 1.5; standard deviation = 0.25; sampling effort = 10; defence costs = 0–0.5 in increments of 0.01; challenge cost = 0.02; search cost = 0.02; stochastic frequency = 2 or 3; stochastic mortality = 2–4. Conclusions: The two strategies frequently co-existed. The pre-emptive strategy outperformed the despotic strategy. Pre-emptive individuals gained additional advantages when resident, and when defence costs were high. Thus, real populations of territorial species are rather likely to also exhibit mixed strategies where respect for property rights may trump overt conflict.
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 | 0.002 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.003 |
| Scholarly communication | 0.002 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.001 |
| Insufficient payload (model declined to judge) | 0.021 | 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".