Cultural learning process: lesson from microhistory
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Purpose The purpose of this paper is to examine the cultural learning process (namely, the development, practice and enhancement of cultural intelligence (CQ)) of a successful entrepreneur – Harold Bixby, a Pan American Airways expatriate, as reflected in the memoir of his experiences in China during 1933–1938. Design/methodology/approach This study adopts a microhistory approach as a methodology for studying history and the past while ultimately requiring evaluations informed by the present. This paper first identifies the literature gap on CQ development and the need to study historical accounts of the past in assessing the CQ development process. This study then outlines the four key foci of microhistory as a heuristic for making sense of on-going and past accounts of selected phenomena. Findings This paper finds that specific personality traits (namely, openness to experience and self-efficacy), knowledge accumulation through deep cultural immersion (namely, extensive reading/study, visiting/observation and interacting/conversation), critical incident and metacognition all contributed to Bixby’s CQ development, which was a time-consuming process. Originality/value The study contributes to debates around cultural learning and historical organization studies by providing a rich, qualitative study of CQ assessment and CQ development through microhistory. This study highlights the importance of cognitive CQ and the function of extensive reading/studying in the process of knowledge accumulation. This paper draws attention to critical incidents as an underexplored way of learning tacit knowledge. Moreover, this study suggests metacognitive CQ can be enhanced through meditative and reflexive teaching and research practices. These findings have significant implications for cross-cultural training programs.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.000 |
| 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) | 0.001 | 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 it