The Complexities of Acculturation and Discrimination of Immigrants in Ireland
Bibliographic record
Abstract
Introduction: The increasing number of multi-cultured immigrants reaching the Republic of Ireland, suggests notable psychological adaptations for the Irish-arrived immigrants, in relation to their ability to acculturate and assimilate in Irish society. This research study explores the relationship between perceived discriminatory experiences and the processes of assimilation and acculturation among Irish immigrants, considering demographic variables (age, gender, ethnicity). Method: This study employs a quantitative, cross-sectional, within-subjects design. A number of 82 participants, have been administered three measured scales, 1) the Acculturation Attitude Scale (AAS), (2) Vancouver Index of Acculturation (VIA), and lastly, (3) Day-to-Day and Major Events Discrimination Scale (EDS) & (MEDS); alongside recording the demographical factors of each individual (age, gender, and ethnicity). Results: The results administered non-significant results regarding all hypotheses identified; two correlational analyses, simple linear regression analyses for each variable, and lastly, two multiple regression analyses. Conclusion: The findings of this study determined non-significant relationship between perceived discrimination and assimilation/acculturation in Irish immigrants. Therefore, suggesting that other factors beyond discrimination influence assimilative and acculturative attitudes among Irish immigrants. Further research is recommended to explore these potential influencing factors in greater depth.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.002 | 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".