Social impact investing as a neoliberal construction: ego and altruism in the post-colonial space of Oaxaca, Mexico
Bibliographic record
Abstract
Purpose This paper examines social impact investing (SII), a growing source of investment from the Global North to the Global South celebrated as a new way of doing good in low-income countries, but bearing elements of neoliberalism that can reify post-colonial contexts. Design/methodology/approach A microfoundational, autoethnographic approach is used based on the author’s experiences and emotional epiphanies while engaged in an activist entrepreneurial enterprise. The author’s goal was to effect positive social change with Indigenous Mexican producers of mezcal liquor. Findings Despite the best of intentions and following best practices for SII, the expected altruistic outcomes were eclipsed by inadvertent post-colonial behaviours. Neoliberal foundations of financialization gave primacy to the perspectives and egos of the investors rather than meaningful impact for the Indigenous beneficiaries. Research limitations/implications Based on the findings, three areas are presented for further research. First, how Global North social impact investors balance the ego of their motivations with the altruism of intended outcomes for beneficiaries. Second, what ownership structures of Global North investments allow for social benefits to flow through to intended beneficiaries. Third, how post-colonial power imbalances can be redressed to give an equal position to Global South beneficiaries as people, rather than financial metrics indicating only that they have become less poor. Originality/value By using autoethnographic methods that expose the vulnerability of the researcher, unique insights are generated on what happens when good intentions meet with a post-colonial context. The neoliberal underbelly of SII is revealed, and ways to make improvements are considered.
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How this classification was reachedexpand
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 | 0.003 |
| 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 | 0.000 |
| 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 itClassification
machine, unvalidatedMachine predicted; a candidate call from one teacher head, 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".