Bibliographic record
Abstract
This paper seeks to define and distinguish the elements required to foster a creative collaboration. Creative collaborations are relationships that combine both personal and professional connections to develop the creative process. As an artist and a teacher collaborative practices have had a profound impact and informed my personal and professional practices. Strong collaborative relationships can have a profound impact on creative development, unfortunately, the elements needed to develop the effective relationships are misunderstood. A process of active interviews was conducted with several artists and educators that I had identified as having participated in successful collaborations. Through the interview process I hoped to find the common features of the collaborative relationship. I hoped to find through this commonality the key to developing a creative working group.
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 | 0.014 | 0.024 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.006 | 0.004 |
| Science and technology studies | 0.016 | 0.012 |
| Scholarly communication | 0.020 | 0.014 |
| Open science | 0.005 | 0.028 |
| Research integrity | 0.005 | 0.003 |
| Insufficient payload (model declined to judge) | 0.052 | 0.009 |
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".