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
After discussion and thought, we agreed that relocation was a subject that applied to almost everyone at SIT and therefore designed a training concentrating on the various aspects of relocation such as types of moves, how they affect the person moving, practical knowledge, the adaptation process and relationship building in a relocation context. The trainers were a group of Euro-American women and the participants were a group of seven U.S. American women and two Canadian women. The training on relocation was intended to afford the participants the opportunity to enhance their skills knowledge and awareness about relocation. By using the knowledge and experiences that the participants had, based on the theories of experiential learning, the participants were able to better understand their past relocations and better assess their future relocation needs. Using the various experiences that the participants had, the training focused on participants' evaluation of previous factors involved in their moves that helped and hindered their relocation process. After re-evaluating past relocations, participants were able to apply new insights to successfully relocate in the future.
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 | 0.000 | 0.000 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.001 | 0.005 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it