Technology’s Influence on the Metaphorical Language in Contemporary Literature: A Transformative Force and a Formidable Challenge
Bibliographic record
Abstract
This study sheds light on the intricate ways technology is reshaping the landscape of metaphorical language in contemporary writing. It delves into the burgeoning trend of aesthetics heavily influenced by technology. By meticulously analyzing a curated collection of visually captivating digital images, the study explores how technical language is used to craft these images and how digital constructs imbue them with a unique character.Furthermore, the study goes beyond imagery, comprehensively examining the influence of technology on characterization and plot structure within contemporary novels. It acknowledges the emergence of characters and narrative elements that are fundamentally driven by technology, exploring how these innovations are shaping the way stories are told and experienced by readers. Ultimately, the study highlights the transformative potential of technology. It recognizes how technology can enrich and expand the metaphorical repertoire available to contemporary writers. However, it also acknowledges the challenges that technology presents in terms of maintaining the nuance and authenticity of language, as well as the potential for the erosion of traditional linguistic values.
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 | 0.001 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| 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) | 0.000 | 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 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".