Bibliographic record
Abstract
I believe particularly the experimentation on new forms of peer review in the conference is a very good contribution to the academic community. I guess most of us who have written a few papers have experienced both very good and less constructive peer review. Having an open peer review during and after a conference creates a structure where there is more pressure on the reviewers to be constructive. The same can be said about the conference itself, with its focus on creating a positive and including environment, and at the same time the relatively smaller size of the conference creating the opportunity to get to know the other attendees.One could potentially fear that the loss of anonymity would limit the will to come with comments pointing to weaknesses, points of improvement, etc., but this is not my experience from the conference at all. In fact, I believe that one of the reviews I got from the conference was one of the most thorough and constructive reviews I have ever gotten. So based on a dataset of one submission, I would suggest continuing to experiment in this direction. The reviews during the conferences with group discussions around tables also ensure a more thorough discussion than in the regular conference setting. There were adjustments made during the conference, and I suggest also continuing to experiment with the exact format, as I believe there is potential in the overarching idea that has not been completely fulfilled, i.e. in assuring a thorough discussion of all papers. In addition, I will applaud the foci on creating a positive conference environment and getting to know the different participants. Although some of the activities might challenge a relatively traditionally-minded academic as myself, challenge is good, and if I remember correctly, it was clearly presented that it was OK to opt out if some things were too challenging. The only fear I have is that the environment at the conference, while welcoming, may become too detached from the more common/general environment in engineering, so as to limit its impact on the field itself. While I see the need for something different, and how it can create breathing space for participants, I also see a parallel to a historic conflict between some traditions within anarchism and other socialists. While it can seem nice to create an autonomous commune of like-minded, it can also limit your capability of creating change in society in general. But I guess this is one of the dissonances we will always have to live with, where you need to find the right balance, and we all need to find a way to bridge what we bring back with us from the conference (and similar venues), to the everyday reality of our own institutions to try and create change there. (communication by email on 2025-04-22)
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 | 0.188 | 0.508 |
| Meta-epidemiology (narrow) | 0.002 | 0.002 |
| Meta-epidemiology (broad) | 0.004 | 0.004 |
| Bibliometrics | 0.004 | 0.004 |
| Science and technology studies | 0.017 | 0.025 |
| Scholarly communication | 0.040 | 0.028 |
| Open science | 0.009 | 0.017 |
| Research integrity | 0.043 | 0.087 |
| Insufficient payload (model declined to judge) | 0.021 | 0.026 |
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".