Bibliographic record
Abstract
Abstract. Defining ecological boundary as an outer envelope of an ecological entity such as an individual, colony, population, community, an ecosystem, or any other discernible unit provides methodological benefits and should thus enhance existing perspectives and research protocols. I argue that, because boundaries are features of entities, the first step in investigation of boundary structure and properties should involve identification of the entity the presumed boundary of interest belongs to. I use a general perspective where ecological systems are parts of a larger system and themselves are made of subsystems (or entities). Such a general hierarchy of ecological objects offers guidance as to how boundaries can be found for specific systems, and how their investigations might lead to reliable and generalizable insights. In particular, it may help in (a) categorizing types of boundaries based on mechanisms leading to formation of entities; (b) deciding what is and what is not a boundary by clarifying the nature of discontinuities seen in nature (e.g., sharp habitat transitions or weak separation of entities); (c) assisting in selecting fruitful resolution at which boundaries are examined; (d) approaching boundaries in complex, nested systems; and (e) deciding what criteria to use in answering questions about a particular boundary type. To facilitate the above I provide general criteria one may use for identifying ecological entities. Such criteria should assist in focusing on boundaries appropriate for a given research question. Finally, where advancing the theoretical framework for ecological boundaries is concerned, the diversity of boundary types will be better served when reorganized in relation to the concept of entity as discussed below.
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 distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.002 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.008 | 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 teacher head, 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".