Book Review: Making and Breaking Settler Space: Five Centuries of Colonization in North America
Bibliographic record
Abstract
claims, whether it be cobalt, copper, diamond, gold, or silver, although the global market value constantly adds layers of conflict.As academics and other commentators have noted, many companies also perceived themselves, or were perceived, as "unpunishable."Emulating political patronage structures, mine sites may present themselves as positive and beneficial while they are exploitative and dangerous to many.More challenging in this globally competitive industry is the influence of China's foreign policy objectives, addressed by several authors in this section.China takes no issue with the sometimes-weak governance of African states and is content to disregard corruption, conflict, or other local social abuses in order to access mines.While not immune to similar charges, Western companies are held to international standards that China is not.INGOs are forcing cleaner definitions, standards, and expectations.Slowly, both local and host investor politics are producing "more nuanced agreements."7 Finally, in their concluding chapter, Andrews, Edward Akuffo, and Grant observe that none of the included case studies point to an ideal mode of natural resources development.Each actor (state, corporation, community, NGO, IGO, INGO) presents various opportunities and drawbacks.Conflicting expectations, intentions, and understandings continue to grossly impede meaningful progress for people across the continent.The Global North's increasing penchant toward the development of industrywide norms for mining sites around the world, while laudable, is still at its core imbued with colonialism and colonial superiority over the resource-rich countries of Africa.Whether natural resource development is a panacea or a Pandora's box remains inconclusive.
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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 | 0.001 | 0.005 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.003 | 0.005 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.004 | 0.004 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.018 | 0.005 |
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".