Bibliographic record
Abstract
Purpose – This paper aims to develop and test hypotheses on determinants of supply chain managers’ salaries. While women make up about half the workforce, there is evidence in the trade press that they receive far less than half of the compensation. Sex of the manager and size of his or her organization are among the predictors of salary. Design/methodology/approach – The hypotheses are tested using regression analysis of data from a survey of supply chain managers in Canada. This technique enables testing for a gender effect, while controlling for the effects of other factors. Findings – Seven variables are found to be significant predictors of supply chain manager salaries. Smaller companies pay lower salaries. Small business supply chain/logistics managers working longer hours with a professional designation, more experience, greater budgetary responsibility and greater share of compensation coming as a bonus earn higher salaries. Finally, male small business supply chain managers earn more than their female counterparts. Research limitations/implications – The piece includes a discussion of limitations and future research opportunities into the gender salary gap. Practical implications – There are implications for small businesses wanting to hire supply chain managers, and for female (and male) managers looking for work. Social implications – This paper presents evidence of possible gender discrimination against half the population. The potential social implications are tremendous. Originality/value – This is a unique piece of research in testing theory-driven hypotheses about supply chain salaries, especially by including gender and organizational size as predictors.
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.
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 | 0.001 | 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 | 0.001 | 0.002 |
| Open science | 0.001 | 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".