Alfred Schutz’s ‘Stranger’, the theory of sociocultural models, and mechanisms of acculturation
Bibliographic record
Abstract
In this article, the author addresses the mechanisms of the acculturation of people who move across different cultural communities (immigrants, refugees, sojourners, international students, etc.). It starts by analyzing Alfred Schutz’s essay ‘Stranger’ and then connects it to the theory of sociocultural models (TSCM) (Chirkov, 2020a). Schutz’s treatise provides background and a conceptual map for articulating the mechanisms of acculturation. The TSCM elaborates on these concepts and hypotheses and justifies the proposed understanding of the psychological and sociocultural basis of acculturation. The primary idea of this approach to acculturation is that migrants experience a clash and tension between two sets of sociocultural models: from their home communities and from their host communities. Newcomers must understand the sources of this tension; in turn, they must reflect on it and then develop strategies for reconciling these two sets of models. During this process, their selves, rationality, reflective capacities, agency and intellectual autonomy become the primary means for their acculturation success.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.001 |
| Science and technology studies | 0.004 | 0.034 |
| Scholarly communication | 0.004 | 0.007 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.002 | 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".