Culture and Museums in the Winds of Change: The Need for Cultural Indicators
Bibliographic record
Abstract
How individuals live their lives, within the context of personal and collective values, expresses their living culture. Societies may be made up of people with different ethnocultural backgrounds, socio-economic profiles or spiritual orientations, but they share certain common cultural frameworks (e.g., democratic governance, rules of law, conventions of business, principles of equity for all, etc.) of what is increasingly a globalized, pluralized, and urbanized present. Culture is often thought of as either the historical traditions of a group, or else as certain types of activities (e.g., dance, theatre, celebrations, rituals, etc.) and objects (e.g., art, artifacts, clothing, etc.). Meanwhile, cultural organizations are characterized as specialized places of expertise that provide selected kinds of experiences and services to the public – normally available for consumption during leisure time. This article argues that the heart of living culture is to be found not in specialized types of objects, leisure-time experiences, ethnocultural traditions, or cultural organizations but, rather, in its processes of human adaptation in a changing world. The author uses the lens of culture to examine how humanity understands and attempts to manage change within its sphere of influence. How can we best measure the cultural well-being of our societies, our organizations, and ourselves? The overarching notion of global/local sustainability provides the grounding point for considering how best to foster a 'culture of sustainability'.
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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 | 0.020 | 0.058 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.010 | 0.010 |
| Science and technology studies | 0.010 | 0.034 |
| Scholarly communication | 0.023 | 0.042 |
| Open science | 0.003 | 0.018 |
| Research integrity | 0.004 | 0.008 |
| Insufficient payload (model declined to judge) | 0.006 | 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".