Open By Default? Concept-Mapping Our Way to Open Access Consensus
Bibliographic record
Abstract
By its nature design thinking combines creative and critical thinking that is imperative to organizing ideas and improving situations. Design thinking allows libraries to take an iterative approach to exploring a complex problem-space, and generate consensus around a potential solution, all while providing artifacts and documentation of the process. In libraries, design thinking is most commonly employed in the design of spaces or services. However, inspired by Open Access Week, we engaged these strategies to collaboratively deconstruct Western Libraries’ current policies related to open access.\nWe invited staff and librarians from Western Libraries and our affiliates to explore how we define open access, and why and how our libraries support it. Using a collaborative concept-mapping approach, all members of the group individually answered each question, and then collaboratively mapped the answers. These concept maps have informed Western Libraries’ new statement on open access practices and policies.\nOur poster outlines this process and displays the resulting concept maps, offering a framework for integrating design-thinking into the process of policy development.
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 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 | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.002 | 0.000 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.008 | 0.004 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.001 |
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".