FILIPINO ACCOUNTANT CAREER GROWTH AND OPPORTUNITIES IN AMERICA AND CANADA THROUGH NCPACA MEMBERSHIP
Bibliographic record
Abstract
This study examines the relationship between the professional advancement of Filipino accountants in North America and their affiliation with the National Council of Philippine American Canadian Accountants (NCPACA). The research indicates that membership in NCPACA offers numerous benefits, including improved job prospects, higher earnings, and increased opportunities for professional growth. The study’s findings have significant implications for employers, professional organizations, and policymakers seeking to support the career advancement of immigrant professionals. This study offers insights for stakeholders seeking to enhance inclusion and diversity in the accounting sector by highlighting the importance of professional associations in promoting career advancement. A quantitative survey methodology was utilized to select a sample of 100 Filipino accountants associated with the NCPACA. Statistical models demonstrated significant correlations between NCPACA membership and career advancement outcomes. The findings indicate that membership in NCPACA mitigates the impact of authority recognition and cultural adaptation on career progression. The findings of this study hold significance for various sectors and industries reliant on immigrant labor, extending beyond the realm of accounting. The study highlights the importance of networks and resources, as well as targeted support systems, for immigrant professionals to advance in their careers. The study’s findings are beneficial for employers, professional associations, and lawmakers seeking to promote the career advancement of immigrant professionals.
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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 | 0.002 | 0.002 |
| Science and technology studies | 0.007 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.001 | 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".