Addressing Power and Space Within Job Design
Bibliographic record
Abstract
The purpose of this study is to explore and synthesize the ways job design influences and is influenced by the power dynamics of social spaces within volunteer boards of directors. Specially, we adopted Lefebvre’s spatial theory to address how power (re)produces board room spaces and how a shift in the structure of space can influence power dynamics on volunteer boards. Using ethnographic research, we observed six board of directors in nonprofit sport organizations over the course of one year with tenets of job design and spatial theory as guiding principles in data collection and analysis. The findings outline three overarching themes, 1) the construction of power through perceived formal and informal boardroom spaces, 2) disruptions of lived space shifts positional power in job design, and 3) disruptions of lived space elevates the voices of those often unheard. The findings are discussed to demonstrate consistency with and development from job design theory by recognizing the relevance of spatial theory in this conversation. In particular, the study contributes to theoretical understanding of the original conceptualization of job design by incorporating elements of Lefebvre’s (1991) spatial theory to recognize and define power within volunteer boardroom spaces. Implications for research and managers are presented.
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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 | 0.008 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.008 | 0.018 |
| Scholarly communication | 0.007 | 0.005 |
| Open science | 0.001 | 0.007 |
| Research integrity | 0.001 | 0.001 |
| 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".