Communication Accommodation Theory and Intergroup Communication
Bibliographic record
Abstract
Abstract Group memberships provide a system of orientation for self-definition and self-reference in the process of relating to and managing social distance with others, and the use of language and communication serve central roles in the processes. In the nearly four decades since its inception as speech accommodation theory, communication accommodation theory has been used in multidisciplinary, multilingual, and multicultural contexts for understanding when, how, and why we, as speakers, accommodate to each other’s languages and styles of communication. In CAT’s theoretical domain, accommodation refers to the ability, willingness, and strategies to adjust, modify, or regulate individuals’ language use and communication behaviors. Specifically, approximation strategies such as convergence, divergence, maintenance, and complementarity are conceptualized in the earlier developmental stages of CAT, with other strategies such as interpretability, discourse management, and interpersonal control added to the list at later stages. With its strong intergroup features, CAT is a robust theory that offers explicit motivational analysis to account for intergroup communication behaviors and intergroup relations. Blossomed initially in a multilingual and multicultural context in Quebec, Canada in the 1970s, CAT connects well with other existing theories on cultural adaptation, intergroup contact, and intergroup relations. Yet, CAT distinguishes itself from other theories as it attends to the interactive communication acts and processes and relates them to other sociocultural constructs, while interpreting and predicting the social, relational, and identity outcomes.
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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 | 0.004 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.003 | 0.011 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 0.001 |
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".