Bibliographic record
Abstract
The creative humanities respond to the creative turn in art, culture, and higher education. In the decades bracketing the millennium, art and culture were instrumentalized to underwrite growth in the creative economy by attracting world-class talent and generating spin-off benefits for hospitality and tourism. Similarly, higher education was retooled to train labour for the creative economy and bring tangible innovations to Canadian communities. These broadscale shifts present pertinent challenges to humanists: we need new theories to critically examine the production, politics, aesthetics, and second-order consequences of culture vis-à-vis the creative economy, and we also need theories and practices that can strategically situate the humanities within neoliberal models for higher education that increasingly prioritize career preparedness, creativity, innovation, and commercialization. Three emergent theories of humanities creativity and innovation – critical creativity, critical making, and meta-creativity – are delineated to showcase how they can be broadly applied to leverage neoliberal discourse to gain access to resources and opportunities while nevertheless championing alternative models grounded in social justice and the social good.
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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.005 | 0.015 |
| Scholarly communication | 0.009 | 0.004 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.047 | 0.008 |
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".