Career Phases in Research Computing and Data
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
The Campus Research Computing Consortium (CaRCC) Staff Workforce Development Interest Group serves to support current Research Computing and Data (RCD) professionals, provide information for people looking to become an RCD professional, and to provide information to institutions looking to establish RCD workforce development programs. The goal of this group is to curate information from existing, successful programs in order to develop leading practices for staff onboarding, training, and development. This paper presents the results of the interest group’s early effort to define the phases of an RCD career from beginning to end, which is the first step in defining a framework and a shared vocabulary to better collect and organize information and resources. The paper defines pre-, early-, mid-, and late- RCD career phases, and activities, as well as the transitions in and out of a phase. The intent is to use these definitions as a basis for future work of the interest group.
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.
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 | 0.039 | 0.045 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.008 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.004 | 0.039 |
| Open science | 0.005 | 0.020 |
| Research integrity | 0.000 | 0.002 |
| Insufficient payload (model declined to judge) | 0.000 | 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 it