From the School Yard to the Conservation Area: Impact Investment across the Nature/Social Divide
Bibliographic record
Abstract
Abstract In the face of planetary crises, from inequality to biodiversity loss, “impact investing” has emerged as a vision for a new, “moral” financial system where investor dollars fund socio‐environmental repair while simultaneously generating financial returns. In support of this system elite actors have formed a consensus that financial investments can have beneficial, more‐than‐financial outcomes aimed at solving social and environmental crises. Yet critical geographers have largely studied “green” and “social” finance separately. We propose, instead, a holistic geography of impact investing that highlights the common methods used in attempts to offset destructive investments with purportedly reparative ones. This involves interrogating how elite‐led ideas of social and environmental progress are reflected in investments, as well as deconstructing the “objects” of impact investments. As examples, we use insights from both “green” and “social” literatures to analyse the social values embedded in projects of financialisation in schooling and affordable housing in the US.
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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 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.006 |
| Scholarly communication | 0.005 | 0.003 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.013 | 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 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".