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
This paper introduces a model for conducting research on living conditions among peoples that have experienced rapid social, cultural and economic change in countries where a non-parallel development has occurred. This model was developed by the researchers of SLICA, A Survey of Living Conditions in the Artic; Inuit, Saami and the Indigenous Peoples of Chukotka, which was initiated by Statistics Greenland in 1997. The point of departure for this model is a critique of contemporary living conditions surveys carried out by national statistical bureaus in economically, technologically and culturally segmented areas. The point of view is that these studies erroneously assume that the populations they investigate are homogeneous, and that consensus concerning individual social and economic objectives exists. This usually leads to research designs and indicators of individual well-being that reflect the dominant culture, or the prevalent way of living and thinking in these countries. The focus of this paper is on the research design of SLICA. The implementation of two important methodological challenges is discussed. Namely, (1) how to secure a contextspecific concept of well-being which also mirrors the life forms and the priorities of the respondents and (2) how to measure impacts of structural change on individual well-being.
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 | 0.003 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.003 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.002 | 0.009 |
| Insufficient payload (model declined to judge) | 0.005 | 0.001 |
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