Awareness of Humanities, Arts and Social Science (HASS) Research Is Related to Patterns of Citizens’ Community and Cultural Engagement
Bibliographic record
Abstract
Why should societies invest resources in humanities, arts, and social sciences (HASS) research? While citizens’ quality of life should be affected by the type and level of cultural amenities they have access to, the broader links between HASS research and its impacts on quality of life attributes can be tenuous because of the research attribution challenge, temporally and spatially linking specific HASS research and its ultimate impact on well-being and society. From a survey of 1920 Canadians, here I report perceived values, awareness of HASS research, threats to quality of life, and levels of community and cultural engagement. The key finding of this exploratory study was that HASS research awareness acted as a powerful predictor of threat perceptions, levels of community activity, and cultural engagement at the local level. It was not, however, a significant predictor of core values. From a theoretical perspective, this is in line with a priori expectations that core values are a precursor to worldviews, threat perceptions, and behaviors. There are very different policy prescriptions for increasing HASS research awareness and, by extension, Canadian citizens’ propensity for cultural and physical engagement, depending on how HASS research awareness affects their threat perceptions, values, and behavior. They include alternatives that focus on experiential learning early in life and adult-oriented awareness-building activities. The strong relationship between HASS research awareness and citizen engagement implies that there are important roles for education and awareness-building activities beyond simply encouraging future consumption of cultural commodities among HASS-aware citizens.
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How this classification was reachedexpand
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.008 | 0.001 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.008 | 0.009 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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; both teacher heads agree on what is shown here.
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".