Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In his recent book entitled Metaphor, Hungarian Lakoff-scholar Zoltn Kvecses translates the tenor-vehicle relationship into a linguistic Great Chain of Being (2002). The primary purpose of the paper is to examine how Canadian metaphors of weather fit into this framework. The first part of the paper presents some theoretical grounding, proceeding from the overt-covert and direct-indirect relationship of tenor and vehicle to Lakoff's cognitive concept of metaphor (1980, 1993). Based on this concept, the linguistic Great Chain of Weather Metaphors is created. The second part of the paper makes an attempt at examining the most typical source and target domains of weather, and, based on a pilot sample, it also looks into conceptual weather metaphors built by mapping at each level of the Great Chain of Weather Metaphors. Furthermore, the analysis tackles the question of conventionality as well as the establishment of a certain hierarchy among the different Great Chain levels through the employment of Ricoeur's Platonic ladder theory (1987) and Lakoff's principle of unidirectionality (1990). This section of the paper is followed by an in-depth analysis focusing on objectto-weather and weather-to-object correspondences.
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.
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) | 0.000 | 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 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it