Abstract metaphorical classes: A perspective from distributed models of conceptual representations
Bibliographic record
Abstract
This article looks at the semantic space of abstract and concrete concepts from the perspective of distributed models of conceptual representations. It focuses on abstract metaphorical classes and the mechanisms through which these concepts are processed. When the metaphor X is a Y is understood, X is included in the abstract metaphorical class of Y. This metaphorical class is abstract because the most of semantic features of Y are filtered out through a suppressiveoriented mode of processing. It is suggested that abstract metaphorical classes of living things are usually defined by a single or a very small set of semantic features. Therefore, such metaphorical classes are highly abstract. On the other hand, abstract metaphorical classes of nonliving things are defined by a relatively larger cluster of semantic features. Therefore, abstract metaphorical classes of nonliving things have a relatively higher degree of concreteness compared to those of living things. In other words, abstract metaphorical classes of living things and nonliving things are rather different in terms of nature and the structure of semantic space.
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 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.048 | 0.003 |
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; both teacher heads agree on what is shown here.
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".