Acculturation Strategies: The Study of Bi-Dimensional and Uni-Dimensional of Filipino Immigrants in Madrid
Bibliographic record
Abstract
In recent decades due to a noticeable increase in migration, there has been increasing scholarly attention given to problems immigrants are facing. It seems that the most significant challenges for immigrants are adapting to the new culture and being part of the new society. However, there are numerous factors that not only may affect the type of acculturation strategy immigrants take advantage of, but also boost adaptation or the other way round, stop them or hinder the adaptation and acculturation process. This paper aims to make a better understanding of the demographical features (age, gender, and level of education) with uni-dimensional and bi-dimensional acculturation strategies. The researcher has used an online questioner (Vancouver Index of Acculturation) for 35 participants (Filipino immigrants) in Madrid, Spain. The author hopes that this paper helps migrants especially Filipinos, who envisage emigration and accommodating in a new society with a new language and culture, to make a better decision for migration concerning gender, age, and educational level in the target country.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.003 | 0.001 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.001 | 0.002 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".