Bibliographic record
Abstract
Although typically applied to entire enterprises, the concept of business models applies to training and performance improvement groups. Business models are “the method by which firm[s] build and use [their] resources to offer…value.” Business models affect the types of projects, services offered, skills required, business processes, and type of respect accorded the training and performance improvement group. Six business models characterize training and performance improvement groups: (a) consulting firm—a group from outside an organization that advises on strategic and performance issues and implements them; (b) internal profit center—an internal group that offers services such as performance consulting and classroom and e-learning courses for a fee and makes a profit; (c) internal cost center—an internal group that provides classroom and e-learning courses and related administration at cost; (d) leveraged expertise—a small internal group of trainers who identify training needed, train subject matter experts to provide it, and handle related logistics; (e) development shop—an external group that develops training programs on contract; and (f) course marketers—an organization that builds courses.
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 | 0.016 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.005 | 0.007 |
| Science and technology studies | 0.003 | 0.005 |
| Scholarly communication | 0.009 | 0.007 |
| Open science | 0.002 | 0.003 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.014 | 0.006 |
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".