Do We Need to Care About Professionals in Order to Mobilize Them? A Data Reanalysis
Bibliographic record
Abstract
According to Julien (1991), there seems to be a feeling of demobilization among the professionals in Quebec’s public service. This feeling is caused, in part, by inappropriate management styles. For instance, professionals tend to express more discontent when their superiors adopt an abdicant management style. As a conclusion, Julien asserts that professionals prefer a directing style to an abdicant style of management. Since these results were not in line with theories (clash of culture, mobilization as a form of behavioural organizational commitment, empowerment), data were reanalyzed in order to shed light on this issue. The typology of management style proposed by Julien was constructed by using two empirical dimensions (concern for the accomplishment of work and concern for employee well being), and one unmeasured dimension (concern for power). By dividing each empirical dimension into three levels (low, medium high), Julien proposed nine different management styles. Given that arbitrary cut-off points were used for dividing empirical dimensions, it is possible that some of the nine styles do not exist empirically. Furthermore, it is possible that using the unmeasured dimension of power in data analysis may affect data results. This provided the rationale for data reanalysis.As explained by Julien (1991: 614), the data for this study were collected in November and December 1987 and in January 1988. A questionnaire was sent to a probability sample of 4,502 professionals, divided in three areas of employment (Greater Quebec City, Greater Montreal and the remaining areas), and in 24 government departments and 48 agencies. This sample was picked at systematic random among some 13,000 professionals, whether or not they are members of a union, and who are under Quebec’s law on public service. No reminder was sent, and the overall reply rate reached 50,8%. The 2,289 professionals who took part in the research are proportionally representative of all the employees of that category, according to details such as sex, age, number of years in service, employment area, size of organization.Julien’s data were subsequently reanalyzed with traditional statistical techniques (such as exploratory factor analysis and cluster analysis) and with modern statistical methods (such as confirmatory factor analysis and structural equations). Cluster analysis showed that only five management styles emerged (instead of the nine identified by Julien). Among the five management styles, the abdicant style was merged with the directing style. Furthermore, data analysis showed that professionals were more dissatisfied with an abdicant/directing style than with any other management style.Since the issue of mobilization was at stake, a model based on Julien’s conceptual framework was tested with structural equations. This model related (1) the two measured management style dimensions (concern for the accomplishment of the work and concern for well being) to (2) professionals’ mobilization through (3) professionals’ satisfaction with management style. Data results showed that professionals’ mobilization was indirectly influenced by the concern expressed by their superiors for employee well being (interest for participation) through professionals’ satisfaction with the human side of superiors’ management style. In other words, satisfaction with management style was more influenced by the concern for employee well being than by the concern for the accomplishment of work (supervision). Furthermore, Julien’s conclusions about professionals’ desire to be controlled need to be interpreted cautiously since the dimension of power was not measured. As a rule, adopting a participative management style and caring for professionals are useful for mobilizing them.
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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 | 0.009 | 0.035 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.013 | 0.013 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.003 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.003 |
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".