Organizational training across cultures: variations in practices and attitudes
Bibliographic record
Abstract
Purpose The purpose of this paper is to provide a synthesis based on a review of the existing literature with respect to the variations in training practices and attitudes across national cultures. Design/methodology/approach A content analysis technique was adopted with a comparative cross‐cultural management perspective as a backdrop to address the occurrence of differences in practices and attitudes across various national cultures. Findings Most of the extant literature remains distant from providing a systematic and analytical repertoire on the subject. In efforts to bridge this gap, a synthesis of the literature has been elaborated, identifying a range of variations that have been grouped around the following categories: importance of organizational training; access to organizational training; different types of training provided to employees; actors involved in organizational training; and organizational support for training. Research limitations/implications The heterogeneity of the literature impeded the use of a theoretical training management framework for the present review. Practical implications Organizations operating overseas and HRM/HRD practitioners should consider the complexity of diverse cultural differences, while managing employee training in culturally diverse settings. Nations ought to be aware of training practices abroad to observe trends and changes caused by globalization, as they may influence the shaping of national training practices and regulations. From a theoretical point of view, it is important to undertake conclusive research by further examining training practices and attitudes through the various national cultures with the objective of better circumventing the differences and by highlighting their prominent characteristics and implications. Originality/value The present contribution is the first documented synthesis of the literature on the subject.
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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 | 0.005 | 0.013 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.001 | 0.002 |
| Scholarly communication | 0.004 | 0.002 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.000 |
| 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".