Bibliographic record
Abstract
The first issue raised by this paper is whether semiotics can bring any added value to ecology. A brief examination of the epistemological status of semiotics in its current forms suggests that semiotics' phenomenological macroconcepts are incommensurate with the complexity of the sciences comprising ecology and are too reductive to usefully map the microprocesses through which organisms evolve and interact. However, there are at least two grounds on which interfacing semiotics with ecology may prove to be scientifically productive: the very looseness of semiotic discourse can be an important catalyser for multidisciplinary interactions, an important condition for the emergence of truly holistic ecology; the present semiotic conceptual apparatus is not carved in stone. All its notions, frames of reference and types of reasoning can evolve in contact with the problems encountered in evolutionary ecological research. Semiotics, as an open-ended epistemological project, remains a proactive intellectual resource. The second issue raised by this paper is precisely to call attention to the opportunity provided by recent developments for rethinking and furthering semiotic inquiry. An attempt is made to show that counterintuitive theories such as memetics and new frontiers in teclmology such as nanotechnology, could help recast ecosentioticsalong more intellectually exciting lines of inquiry than the mere rewriting of ecological discourse in terms of the traditional semiotic macroconcepts. It goes without saying that memetics and nanotechology are not presented here as definitive solutions but simply as indicative of possible directions toward acomprehensive evolutionary ecosentiotics that would radically transform the basis of the 20th century sentiotic discourse and its ideological agenda.
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 | 0.004 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.002 | 0.025 |
| Scholarly communication | 0.008 | 0.013 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".