Things that Can Go “Wrong”: Finding Our Own Way in Graduate School
Bibliographic record
Abstract
Graduate school was not designed for most of us. Students from marginalized backgrounds (BIPOC, LGBTQ+, certain socioeconomic backgrounds, those with disabilities) are less likely to have information about graduate school and academia, making them more likely to face challenges in navigating gatekeeping and moving through program requirements. While facing these obstacles, it might feel like something has gone “wrong.” This chapter challenges that framing and guides how to make choices when: changing your dissertation, subfield(s), and advisor; transferring programs; working additional jobs; taking a leave of absence; and caring for your mental health. This manuscript is part of Strategies for Navigating Graduate School and Beyond, a forthcoming volume for those interested in pursuing graduate education in political science (Fall 2022 publication).
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 | 0.020 | 0.039 |
| Meta-epidemiology (narrow) | 0.000 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.032 | 0.024 |
| Scholarly communication | 0.019 | 0.018 |
| Open science | 0.002 | 0.019 |
| Research integrity | 0.008 | 0.018 |
| Insufficient payload (model declined to judge) | 0.014 | 0.004 |
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".