Contingent workers: needs, personality characteristics, and work motivation
Bibliographic record
Abstract
Purpose This paper seeks to challenge the claim that traditional and non‐traditional employees differ significantly in terms of their needs, personality characteristics, and work motivation patterns, by surveying management consultants in Canada. Design/methodology/approach The study is based on a quantitative online survey undertaken among 204 Canadian management consultants in 2008, representing both traditional employed consultants, contingent consultants, and company representatives. Findings The study demonstrated no significant differences with regard to needs, motivation, and personality characteristics between traditional and non‐traditional employed management consultants, which means that no significant changes to existing human resource management policies seem to be needed. Originality/value The existing literature on contingent employees' needs, personality characteristics and work motivation has mainly been devoted to the study of differences between traditional and non‐traditional work arrangements seen as single groups. This study extends and complements the understanding of the underlying dimensions of both the explicit and the implicit contract within the contingent management consultant‐organization relationship in order to explain the influence of these dimensions on the human resource management strategies. The underlying assumption is that non‐traditional work arrangements vary according to the type of job and the context in which the job is performed.
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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 | 0.001 |
| Science and technology studies | 0.002 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.002 | 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".