Bibliographic record
Abstract
Like others who have studied the concept of creativity in depth and failed to arrive at a consensus, my research showed that students-even those who have enrolled in a program with an artistic dimension such as fashion design-do not agree on a definition either.In the first class, therefore, I ask them for written answers to the following questions:• How do you define creativity?• How do you tap into your creativity?• What do I really want when I ask you to be creative?Convergent analyses (Kao, 1998 and Florida, as reported by Hochereau, 2006) confirm that we have gone from an industrial era to a time of creativity.At present, our society is facing significant challenges that require original solutions.Employers are looking for the most creative candidates, regardless of trade or profession (Edwards et al., 2006).Quebec's Department of Education, Recreation, and Sport (MELS) has asked CÉGEPs to introduce five college-level skills, including one called "exercising creativity" (Cégep Marie-Victorin and the MELS's Direction de l'enseignement au collégial, 2010).Accordingly, it is paramount that we help our students understand what creativity actually means, and how it can be put to best use.Studies conducted in Quebec and elsewhere show that, when attempting to define creativity, we are not all talking about the same thing (Edwards et al., 2006;Goetgheluck, 2008;Labelle, 2001;Murray, 2004;Oliver et al., 2006).Because researchers cannot seem to arrive at a common definition of the concept, "creativity" is still poorly defined, and it is difficult to establish a consensus based on the many definitions that do exist.
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 | 0.004 | 0.004 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.003 | 0.023 |
| Scholarly communication | 0.017 | 0.006 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.002 | 0.004 |
| Insufficient payload (model declined to judge) | 0.013 | 0.003 |
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".