Bibliographic record
Abstract
In this book we have critically but constructively reviewed the state of the art regarding languages in contact (bilingualism), from individual bilingualism (or bilinguality) to societal bilingualism. We began by examining traditional and current definitions of bilingualism, none of which was found to be adequate. They all show one or more of three main weaknesses. First, they are unidimensional : they describe the bilingual in terms of one dimension, such as language competence, ignoring other equally important aspects. Second, they fail to take into account the different levels of analysis , from individual to societal. Finally, they are not based on a general theory of language behaviour . To remedy these failings we proposed a multidimensional theoretical model of language behaviour (Figure 1.1), which we also apply to bilingual behaviour and which guides us throughout the book. According to this model language processing operates at different levels of organisation which are embedded in one another, from micro- to macro-levels: these are the individual networks, the interpersonal networks, the social networks and the social structures. These levels are not independent of one another but are in dynamic interaction. Within and between these levels there are complex mappings of the forms of language behaviour onto the functions they are supposed to serve. It should be stressed that the social and the psychological dimensions are found at every level simultaneously, in the sense that any speaker is at one and the same time an individual, a member of social networks and groups, and part of the whole society. These different levels of language processing require different types of analysis at the individual, interpersonal and societal levels.
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 | 0.003 | 0.009 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.003 | 0.002 |
| Scholarly communication | 0.006 | 0.005 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.003 |
| Insufficient payload (model declined to judge) | 0.116 | 0.043 |
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".