Indigenous Archaeology in Sweden: Aligning Contract Archaeology with National and International Policies on Indigenous Heritage
Bibliographic record
Abstract
This doctoral thesis examines the challenges and potential improvements in managing archaeological projects related to the Sámi people in Sweden. The focus is on aligning practices of contract archaeology with national and international policies for managing Indigenous cultural heritage. The research identifies five key challenges in Swedish archaeology: defining Sámi heritage sites, determining responsibility for relevant expertise, managing Sámi-related information, establishing processes of contract archaeology acceptable to all stakeholders, and deciding whether Sámi and "Swedish" heritage should be managed together or separately. The study compares the approach in Sweden with practices in Norway and British Columbia, Canada, to explore potential solutions. Different systems for cultural heritage management are analysed alongside interviews with archaeologists, Indigenous community members, officials, and other stakeholders, to map success factors and pitfalls of Indigenous cultural heritage management. The study highlights the slow implementation of the United Nations Declaration on the Rights of Indigenous Peoples (UNDRIP) in Sweden and the lack of legislation ensuring Sámi involvement in archaeological projects. The research suggests that addressing these challenges will require re-evaluating current practices, including developing clearer guidelines for managing Sámi heritage sites, improving collaboration between archaeologists and Sámi communities, finding ways to include intangible aspects of cultural heritage within cultural heritage management, and potentially delegating more authority in cultural heritage management to the Sámi Parliament. The thesis concludes by proposing strategies to better align Swedish contract archaeology with national and international policies on Indigenous cultural heritage, emphasizing the need for a balanced approach that respects Indigenous rights while addressing concerns in archaeological practice. These recommendations aim to ensure that Sámi cultural heritage is managed respectfully, acknowledging its unique history and perspectives, while facilitating effective collaboration among all stakeholders involved in archaeological projects.
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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 | 0.028 | 0.025 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.004 | 0.005 |
| Science and technology studies | 0.016 | 0.016 |
| Scholarly communication | 0.025 | 0.008 |
| Open science | 0.002 | 0.015 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.003 | 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".