Indigenous Rights in Scandinavia: Autonomous Sami Law
Bibliographic record
Abstract
Introduction / Christina Allard and Susann Funderud Skogvang -- Themes and reflections: a perspective from canada -- Nigel bankes -- A comparative gaze with aotearoa New Zealand / Jacinta Ruru -- Sami law in late modern legal contexts / Kjell A. Modéer -- Some characteristic features of Scandinavian laws and their influence on Sami matters / Christina Allard -- Reforming Swedish Sami legislation : a survey of the arguments / Bertil Bengtsson -- Sami reindeer herders' herding rights in Norway from the 19th century to the present day / Kirsti Strøm Bull -- The Swedish state's legacy of Sami rights codified in 1886 / Johan Strömgren -- Sami hunting and fishing rights in Swedish law / Eivind Torp -- Local community right to fish : a Sami perspective / Susann Funderud Skogvang -- The legal organization of Sami reindeer herding and the role of the SIIDA / Kristina Labba -- The definition of a Sami person in Finland and its application / Tanja Joona -- To what extent can indigenous territories be expropriated? / Mattias Ahrén -- The rapidly evolving international status of indigenous peoples : the example of the Sami people in Finland / Leena Heinämäki -- Sami legal scholarship : the making of a knowledge field / Eva-Maria Svensson
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 | 0.002 | 0.002 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.005 |
| Science and technology studies | 0.011 | 0.014 |
| Scholarly communication | 0.014 | 0.003 |
| Open science | 0.001 | 0.005 |
| Research integrity | 0.004 | 0.002 |
| Insufficient payload (model declined to judge) | 0.008 | 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 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".