Facility, Location and Employer-Employee Relations of German-Canadian Businesses in Canada
Bibliographic record
Abstract
The purpose of this paper is an investigation into aspects of the decision-making process of German-Canadian business owners regarding the reasons for their choice of location and their assessment of the differences of some major traits of German and Canadian employees. This paper presents the results of a questionnaire that was administered by mail to German business owners in Canada. The purpose of this focus is to provide regional planners with some understanding why German owners/managers choose specific provinces or sites, and to provide managers in Canada with information concerning differences in traits of German and Canadian employees. The results of this work are that location decisions are mostly personal when it comes to choosing Canada as a country for their business, but the more we zoom into the chosen province and the specific site, the more business-related features become relevant. As far as personnel evaluations by German managers are concerned, the key result is that while at first glance it may appear that Canadians and Germans (and, by extension, Canadian and German employees) are not very different culturally, they actually are. Whereas some results appear to support common stereotypes, e.g., Canadians rank higher when it comes to politeness and tolerance, while Germans excel in job knowledge and punctuality, others are more unexpected. Among them are the results indicating no significant differences when it comes to flexibility, ambitiousness, and the acceptance of authority.
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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 | 0.004 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.003 |
| Science and technology studies | 0.008 | 0.002 |
| Scholarly communication | 0.003 | 0.000 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.005 | 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".