New horizons in print: A synthesis of primary sources
Bibliographic record
Abstract
Abstract Over the past 25 years the New Horizons International Music Association (NHIMA) has grown from its roots as a local programme in Rochester, New York, to an international organization that comprises more than 200 programmes touching thousands of participants in the United States, Canada, Australia and Europe. The organization’s unique mission and older adult population have offered expanded opportunities for research, but no review has exclusively focused on the literature related to New Horizons music populations. The authors identified 64 articles, book chapters and dissertations that have investigated questions related to participation in these programmes. They categorized the NHIMA-based publications into three overarching strands: (1) research literature from research journals (n=35), dissertations (n=12), book chapters and conference proceedings (n=10), (2) articles for practitioners from periodicals such as the Music Educators Journal and the Instrumentalist (n=7) and (3) semi-annual newsletters published by NHIMA from 2004 to 2016. This review focused on the research articles, dissertations and the newsletters. A consideration of studies offered insights into who has been researched and the programmes in which they participate. Psychosocial constructs have emerged as integral to New Horizons research and comprise the roles and nature of social interaction, identity formation, motivation and perceived musical, social and health benefits. Finally, an analysis of studies that have investigated pedagogical concerns revealed trends, best practices, resources and approaches that New Horizons programmes have utilized over the last quarter of a century.
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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 | 0.014 | 0.063 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.003 | 0.001 |
| Bibliometrics | 0.053 | 0.065 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.029 | 0.004 |
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".