Utilisation de lunettes munies d’une caméra et d’un microphone pour évaluer l’expérience muséale
Bibliographic record
Abstract
Abstract: We analyse through a case study the potential of wearing camera and microphone-equipped glasses in a museum to assess a visitor’s in situ museum experience. The qualitative analysis of gathered audiovisual data confirms that such a device does facilitate the assessment of the descriptive, appreciation, interactions and environment. Discussion of the strengths and weaknesses of such a device in the context of museum assessment.KEYWORDS: Museum evaluation; visit experience; glasses; audio-visual elementRésumé: A partir d’une étude de cas, nous analysons le potentiel du port de lunettes munies d’une caméra et d’un microphone lors de la visite d’une institution muséale pour évaluer in situ l’expérience muséale d’un visiteur. L’analyse qualitative des données audiovisuelles recueillies permet d’affirmer qu’un tel dispositif favorise l’évaluation de la signalétique, de l’appréciation, des interactions, et finalement de l’environnement. Les forces et les faiblesses de l’usage de ce dispositif en évaluation muséale sont discutées.MOTS CLES: Évaluation muséale; expérience de visite; lunettes; données audiovisuelles
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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 | 0.006 | 0.011 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.002 | 0.003 |
| Scholarly communication | 0.003 | 0.002 |
| Open science | 0.001 | 0.003 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.008 | 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".