Bibliographic record
Abstract
A famous rock anthem of the 1980s by the group U2, entitled I Still Haven't Found What I'm Looking For, had been released the year before I was born. However, contrary to the song's title, I did manage to find a job. As a fresh PhD graduate, I lived the challenges and struggles that graduate students face on a daily basis. Graduate school could be one of the most stressful (but also one of the most rewarding) periods of a young adult's life. Speaking to my peers, I realize that all of them are worried about their long-term employment projections. Without a concrete plan, most of us resort to the traditional route, including 1 or 2 postdocs, in hopes for a miracle, which is usually a tenure-track academic position. But, we know that these positions are scarce and very difficult to obtain. Many of us enter graduate school as naive and ambitious students who seem ready to tackle the world's most pressing problems. Unfortunately, we usually end up with a turbulent landing. The reality is that we struggle to conceive and perform difficult and complicated experiments and generate and interpret data. This is the easy part. Then, we start fighting with journals and reviewers for publishing. Early slaps in the face from editors and reviewers can be very discouraging and painful. At the end of each long day, we go home wondering: is this what we really want to do for a living? Can we take this punishment for another 4 or more years? Harsh criticisms from the supervisor can often exacerbate our existing misery. This is when doubts about pursuing a scientific career start to develop. But, graduate school should not be just about completing experiments and writing papers. It should be a transition from a young and naive individual into a mature and confident professional. So, is there a way to get some help for this transition?
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 | 0.007 | 0.017 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.011 | 0.002 |
| Scholarly communication | 0.010 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.003 | 0.006 |
| Insufficient payload (model declined to judge) | 0.086 | 0.048 |
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".