Idea Work Beyond Organizational Boundaries: Framing and Reframing Projects on a Crowdfunding Platform
Bibliographic record
Abstract
Abstract The process of generating creative outcomes inherently involves tensions, such as the need to simultaneously pursue novelty and usefulness. Idea work serves as a process theory that focuses on managing tensions to achieve creative outcomes. To navigate these tensions and reach creative outcomes, idea work involves a collective process of receiving diverse feedback and iterating revisions. Studies indicate that exploring activities beyond organizational boundaries is crucial for idea work, as they are less constrained by existing routines and structures. Recently, online platforms have been gaining attention as spaces that facilitate interactions among actors across boundaries. In online platforms, the pivotal factor for achieving creative outcomes lies in framing/reframing, effectively communicating ideas to the targeted consumers in a manner they perceive as creative. This leads to the question: How do actors involved in crowdfunding interact and undertake creative revisions through the (re)framing of projects? To answer this, we analyzed a reward-based crowdfunding platform in Japan. We conducted semi-structured interviews involving a total of 36 participants, including project founders and platform operator employees. Our analysis reveals three approaches to reframing projects by founders and curators, aligning with different project stages: reconnecting, refocusing, and reflecting. These approaches shed light on crowdfunding as a space that mediates project founders, curators, and backers to (re)frame projects through their interaction. They also explore how this interaction helps sustain tensions between novelty and usefulness, as well as between commercial viability and social impact, in the creative process of crowdfunding.
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 | 0.000 | 0.001 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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; a candidate call from one teacher head, 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".