New in town, already settled in: Assessing the behavioural and experiential indicators that lead to acculturative advantages
Bibliographic record
Abstract
We supplement extant literature on acculturation by introducing a new construct – individual acculturation action profile (IAAP) – consisting of a configuration of behavioural and experiential indicators that reflect an individual’s previous and current contact with and participation in other cultures. We operationalise each IAAP indicator individually, and the IAAP construct as an aggregated index (IAAPi), by assigning different weights to each construct indicator based on the magnitude of its theorised influence. We distinguish the antecedents of IAAP at multiple levels. Whilst contextual factors are likely to enhance or hinder people’s participation in other cultures, we propose a taxonomy that addresses the dynamism between context and individual initiative. This article thereby expands literature on acculturation, offering notable implications for advantageous acculturative processes and outcomes. The proposed operationalisation of the IAAP construct at the acculturation–organisation nexus can be applied to study many walks of society and outcomes at multiple levels.
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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 | 0.002 | 0.008 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| 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".