Social support and employee job satisfaction : what does the public service employee survey tell us?
Bibliographic record
Abstract
Projects managers, along with any other person having to supervise personnel, must display basic humanistic behavioral competencies (i.e. actions) in order to contribute to employee job satisfaction. Among these competencies, the ability to give support to team members is considers as paramount. However, both employee job satisfaction and supervisory behavior are multi-faceted constructs which still have to be studied and refined further in the public service, especially with regards to their relationship to one another. Therefore, the aim of this thesis is to further our comprehension of these constructs and of their interrelations. Raw data, gathered by Statistics Canada in 1999, 2002, and 2005 through the PSES (Public Service Employee Survey), which deals with the qualities of work environment will be used here. One of the limits of the PSES that needs to be addressed is the absence of a supporting theoretical model. A careful examination of the items and preliminary factorial analyses show that Karasek's Job Demand-Control-Support JDC(S) model offers a conceptual framework which is highly compatible with the PSES. It will therefore be used here both to generate research questions and to interpret the results. The research questions are as follows : 1) What is the factor structure of the PSES and is it stable across cohorts? ) Are items dealing with supervisory and peer support included in one broad social support factor or are they separate factorial entities? 3) Does the perception of supervisory and peer support evolve from T1 to T3 (i.e. 1999 - 2002 - 2005)? 4) Among all the factors generated through factorial analysis of the Public Service Employee Survey, is social support the most strongly related to employee job satisfaction? The three samples taking part in the study represent at least 55% of all federal Public Service employees, with corresponding data sets, including each time more than 100 000 participants.Results indicated that : -A sturdy four-factor solution, conceptually named opportunities, social support, standards and employee job satisfaction exists across the two last survey years (i.e. 2002 and 2005). -Supervisory and peer support are clearly separate and distinct entities and not part of one broad social support factor. - There has been a decrease in employees' perception of supervisory and peer support from a highpoint in 1999. - There is a clear link between job satisfaction and social support in the Public Service of Canada (PSC). Additionally, the employee job satisfaction scale can be split into two conceptually different subscales named stressors and job quality using the items negative and positive loadings, respectively. Implications of these findings are discussed in terms of their applicability in the public service of Canada workforce.
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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 | 0.005 | 0.015 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.004 |
| Science and technology studies | 0.000 | 0.001 |
| Scholarly communication | 0.002 | 0.002 |
| Open science | 0.001 | 0.001 |
| Research integrity | 0.001 | 0.001 |
| Insufficient payload (model declined to judge) | 0.001 | 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".