Bibliographic record
Abstract
This paper presents the outcomes of a pilot study that explores expressions for cardinal directions in Tshiluba, a Bantu language primarily spoken in the Democratic Republic of the Congo. Language data were collected from a native Tshiluba speaker using three elicitation methods and an online dictionary. The results reveal several potential nomenclatural strategies and conceptual sources that Tshiluba uses to linguistically encode cardinal directions, including references to body parts, geographical and environmental landmarks and features, and celestial bodies and events. Meanwhile, a comprehensive exploration of the inherent characteristics of these Tshiluba cardinal direction expressions remains a subject of further investigation. The paper also includes reflections and suggestions regarding research methodologies on this topic. This paper contributes to cross–linguistic exploration and documentation of cardinal direction expressions, both within and beyond the Bantu language family. It also encourages further research on spatial language as a whole, which is a pursuit of great importance in advancing our understanding of human spatial cognition and our interactions with the external world.
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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 | 0.001 |
| 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".