Bibliographic record
Abstract
We explore the language of economics from the perspective of the relation between signs, language and ideology. The focus is on social reproduction in global communication. From the epistemological viewpoint linguistics and economics are interrelated, both are sign sciences and value sciences. Saussure’s general linguistics is modelled on economics, particularly marginalist “pure economics” from the Lausanne school. In the 1960s Rossi-Landi reconsiders the relationship between linguistics and economics, specifically political economy in the Smith-Ricardian and Marxian tradition. In this context linguistic value is not limited to the market, the synchronic axis, and confused with price. Critical of both Saussure’s Cours de linguistique générale and of Wittgenstein’s interpretation of “meaning” as “use”, Rossi-Landi (1966, 1968) – who can be reread today in light of globalized communication as proposed by A. Ponzio (2008) – investigates the production processes of linguistic value applying the theory of labour-value, thus speaker “linguistic work” accumulated in fixed capital (language) from one generation to the next. Thematization of the relationship between linguistics and economics contributes to understanding the concepts of “sign fetishism” and “sign materiality,” while the theory of “language as work and trade” and of “ideology as social planning” throw light on the question of “social alienation”, which in the language of the sign sciences is also “linguistic alienation” and more generally “sign alienation”.
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 | 0.002 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.017 |
| Scholarly communication | 0.006 | 0.009 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.010 | 0.002 |
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".