Subalternity and Language: Overcoming the Fragmentation of Common Sense
Bibliographic record
Abstract
Abstract The topics of language and subaltern social groups appear throughout Antonio Gramsci's Prison Notebooks. Although Gramsci often associates the problem of political fragmentation among subaltern groups with issues concerning language and common sense, there are only a few notes where he explicitly connects his overlapping analyses of language and subalternity. We build on the few places in the literature on Gramsci that focus on how he relates common sense to the questions of language or subalternity. By explicitly tracing out these relations, we hope to bring into relief the direct connections between subalternity and language by showing how the concepts overlap with respect to Gramsci's analyses of common sense, intellectuals, philosophy, folklore, and hegemony. We argue that, for Gramsci, fragmentation of any social group's 'common sense', worldview and language is a political detriment, impeding effective political organisation to counter exploitation but that such fragmentation cannot be overcome by the imposition of a 'rational' or 'logical' worldview. Instead, what is required is a deep engagement with the fragments that make up subaltern historical, social, economic and political conditions. In our view, Gramsci provides an alternative both to the celebration of fragmentation fashionable in liberal multiculturalism and uncritical postmodernism, as well as other attempts of overcoming it through recourse to some external, transcendental or imposed worldview. This is fully in keeping with, and further elucidates Gramsci's understanding of the importance of effective 'democratic centralism' of the leadership of the party in relation to the rank and file and the popular masses.
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 | 0.015 | 0.015 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.013 | 0.108 |
| Scholarly communication | 0.013 | 0.019 |
| Open science | 0.002 | 0.024 |
| Research integrity | 0.003 | 0.007 |
| Insufficient payload (model declined to judge) | 0.004 | 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 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".