<scp>C</scp>o‐Constructing Colonial Dichotomies in Female Former Colonizers' Narratives of the<scp>B</scp>elgian<scp>C</scp>ongo
Bibliographic record
Abstract
Focusing on interviews with female former colonials in theBelgianCongo, we analyze the ways in which the interviewees co‐construct and negotiate their identities in relation to master narratives of colonization in their interactions with the interviewer, who is also a former colonial. We focus mainly on stories of the household and family life, since the colonial household is typically a locus of encounters between the white female colonizers and black household staff. The findings demonstrate a polarization between blacks and whites that is in line with colonial ideological views in which indigenous people are infantilized, thus legitimizing colonization as an endeavor of civilization. These interview narratives thus seem frozen in time, even though they were told more than four decades afterCongolese independence. We propose that this frozen‐in‐time quality is partly attributable to features of the interactions, in which the interlocutors set up a local in‐group of white former colonizers; but it is also a reflection of contemporaryBelgian society, in which a broad and critical debate concerning colonial history, one in which the voices of the former colonizers and the formerly colonized can both be heard, is largely absent.
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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 | 0.002 | 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 | 0.010 | 0.015 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.002 | 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".