Bibliographic record
Abstract
Abstract Objective – This research project sought to elucidate some of the information searching behaviours of directors/conductors of performing music ensembles when selecting repertoire for performance. Of particular focus was the kind of information needed to select repertoire and where that information was sought and acquired. Methods – Semi-structured, guided interviews were undertaken with three conductors from varying musical ensemble forms (choral, orchestral, and wind). This included a graphical elicitation exercise following Sonnenwald’s concept of information horizon maps. A narrative analysis was done, and recurring themes were sought in the various responses to questions and created drawings. Results – The results indicated that directors make significant use of historical and print resources in creating personal lists of repertoire for current or future use. Professional connections for discussion of new or less well-known repertoire were also very important. One particularly interesting outcome was the non-temporally bound nature of conductors’ information searching behaviour, as the current models of information behaviour primarily relate to temporally bound searches. The Internet was noted by the three conductors not as an information source in and of itself but rather as an extension of other information sources. Conclusions – This research highlighted the atemporal nature of information searching behaviour in music directors and suggested a similar aspect in the broader information search process. It indicated a need for libraries that cater to performers to maintain historical lists of varying types (e.g., concert programs, similar lists created by other prominent members of the community, and other types of repertoire lists). Additionally, maintaining community connections and knowledge of new or newly available repertoire is important.
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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 | 0.004 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.004 | 0.001 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".