Invisible Losses and the Logics of Resettlement Compensation
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
The necessity of compensating people negatively affected by conservation and other development projects has been widely acknowledged. It is less widely acknowledged that because conventional compensation assessments focus on material resources and their economic equivalents, many important losses incurred by resettlers are invisible to project authorities. Through ethnographic observations and interviews, we documented losses identified by people facing resettlement from Mozambique's Limpopo National Park. We also examined resettlement planning documents to determine why decision makers' assessments of natural resource use and value neglect losses residents identified as critical. Identifying, preventing, and mitigating invisible losses in resettlement planning necessitates a better understanding of intangible benefits residents derive from resources, which are often as or more important than their readily apparent material properties. These benefits include but are not limited to decision-making authority linked to owning land versus having the use of fields; ancestral identity and social belonging linked to gravesites; the importance of tree roots that provide a powerful sense of security because they suppress hunger in periods of scarcity; and the importance of people's location within social networks and hierarchies as they determine the benefits versus risks that will be incurred through resettlement.
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 | 0.001 | 0.001 |
| 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 | 0.001 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| 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