The Social Consequences of Traditional Religion in Contemporary Africa
Bibliographic record
Abstract
In most of Africa, traditional supernatural beliefs, including beliefs in witchcraft, black magic, or fetishism, are widespread and have remained so despite the spread of Christianity.The effects of these beliefs remain unclear.Some have hypothesized that these beliefs are beneficial and help to sustain cooperative behavior in a setting where the state is often absent.Others have documented that, inconsistent with this argument, such beliefs are negatively associated with economic and social wellbeing.We contribute to a better understanding of the causal effects of traditional supernatural beliefs by using lab-in-the-field experiments in the Democratic Republic of the Congo.Participants complete a range of experimental tasks where one player chooses whether to act in a prosocial manner towards another player.Participants are randomly assigned to another player that has either strong or weak traditional supernatural beliefs, and this information is known by the players.We find that participants act less prosocially towards randomly-assigned partners who have stronger traditional beliefs.We find that antisocial behavior is viewed as being more acceptable when it is directed towards those with stronger traditional beliefs.Consistent with both of these effects, we also find that individuals hold a wide range of negative perceptions and stereotypes about those holding strong traditional beliefs.
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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 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.001 | 0.001 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.003 | 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".