Bibliographic record
Abstract
The Problem. Human Resource Development (HRD) scholars and practitioners need to address the problem of conceptualizing HRD in various community settings. The Solution. To address this need, the authors conducted a case study research to explore the role of HRD in developing the Ismaili community in Minnesota. Data analysis revealed four themes: (a) conceptualization of HRD in the Ismaili community of Minnesota, (b) history and examples of HRD efforts in this community, (c) the role of women in the community’s HRD efforts, and (d) the future of HRD in the Ismaili community of Minnesota. The use of HRD within this community was heavily focused on societal development of the community. The Stakeholders. Recommendations for HRD practice (practitioners) and research (researchers) suggest that HRD, especially within religious communities (members and leaders of such communities), be explored with an open mind for the purpose of creating a pluralistic and civil society (all citizens).
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.007 | 0.011 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.011 | 0.030 |
| Scholarly communication | 0.009 | 0.009 |
| Open science | 0.002 | 0.020 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.020 | 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".