Museums as media: the social and communicative aspect of museum practices
Bibliographic record
Abstract
This article conceptualises museums as a distinct form of media. The author tries to examine how contemporary museums are transformed under the pressure of addressing urgent socio-communicative challenges. The study is theoretically founded on the ideas of the Toronto School of Communication, particularly the works of Harold Innis and Marshall McLuhan. Within this framework, classical museums are interpreted as media transmitting cultural and historical messages; they are characterised as time-biased and “cold” media. Furthermore, the article describes museums as “passive” and “integrative” media. It is argued that the historical trajectory of museums reflects a development from time-oriented to space-oriented media (space-biased media), and from “cold” to “hot” media. The communicative environment of museums is becoming increasingly active through the introduction of various communicative technologies. It is described historically, how the communicative space of museums has undergone several revolutionary transformations. Firstly, there was the transition from private closed collections to public exhibitions. Secondly, there has been the qualitative diversification of museum profiles and the quantitative expansion of museum collections. Thirdly, museums have expanded the internal media through the implementation of immersive and interactive technologies, facilitated by the convergence of different media forms. Fourthly, there has been the external media expansion and globalisation of museum communications through the emergence of the “Internet galaxy”. The complexity of decoding museum messages is also examined. Decoding is interpreted through the lens of symbolic interactionism as the necessity of understanding and immersing oneself in the symbolic world and meanings conveyed by cultural artifacts. Following Riepl’s Law, it is further posited that virtual museums have found their own niche and are unlikely to supplant classical museums.
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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 | 0.003 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.004 | 0.003 |
| Science and technology studies | 0.010 | 0.036 |
| Scholarly communication | 0.020 | 0.013 |
| Open science | 0.001 | 0.012 |
| Research integrity | 0.002 | 0.002 |
| Insufficient payload (model declined to judge) | 0.005 | 0.000 |
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".