Bibliographic record
Abstract
Abstract This paper reports on the findings of a study examining how theatre professionals (actors, directors and others) make sense of the works of a culturally iconic author (William Shakespeare). The findings of the study are based on interviews with 35 theatre professionals in Canada, Finland and the UK. The study aims a more holistic approach to the study of information behaviour, one which acknowledges the complexity of sense‐making as more than the problem‐solving behaviour of individuals – as an embodied, social process, involving emotion as well as rationality. In doing so it draws on theoretical approaches from a range of different disciplines and traditions, including Dervin's Sense‐Making, Foucault's discourse analysis and Derrida's deconstructionism. Rather than active searching, the focus of most information research, the events that participants described as having the greatest influence on their understanding of Shakespeare were informal ‘social’ interactions. Participants in the study frequently explicitly linked their engagements with texts to their interactions with other people. Participants frequently described the significant influences on their constructions in terms of long‐term relationships – with other people and with the written work of authors. For theatre professionals, understanding Shakespeare involved much more than a cerebral process: their professional lives are based on the ability to embody their knowledge: they need to manifest their understanding in the physical world as physical actions in physical space. The study demonstrates the need for information behaviour research to expand its focus beyond active information seeking and searching and to devote greater attention (both theoretical and empirical) to such factors as: informal knowledge‐sharing; sense‐making as an affective as well as a rational process; and embodiment as a central aspect of information use.
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 | 0.012 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.023 | 0.035 |
| Scholarly communication | 0.013 | 0.009 |
| Open science | 0.002 | 0.010 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.003 | 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".