Governance of forests and governance of forest information: Interlinkages in the age of open and digital data
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
Policy processes to open digital forest data and information are driven by expectations of increased effectiveness and efficiency of forest management, greater transparency of forest decision making, development of new innovations, and transition to bioeconomy. We investigate how interlinkages between the governance of forest information and governance of forests are being reshaped in the formation of new institutions for open data and information in the case of Finland, where the Forest Information Act was revised in 2016–2018. A qualitative content analysis of public statements related to the legal reform was conducted to understand the perceived benefits and risks associated with more open forest data and information by different actors, and how those perceptions shape their views on appropriate governance of forest information. The analysis reveals conflicts between right to information and right to privacy; concerns about data format, access and usability; as well as the interests of actors with entrenched positions in Finnish forest governance. The debate on opening forest information reflects tensions related to a transition towards greater openness and diversity of values in the forest sector. We envision further research on the relationship between the governance of forests and governance of forest information to support informed decision making during the current open data boom.
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) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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