Hemarbete och organisationsidentitet: En kvalitativ studie om hur Uppsala kommuns organisationsidentitet bevaras och återskapas
Bibliographic record
Abstract
The purpose with this essay is to understand what happens with the organizational identity at a Swedish municipality when employees work partly from home. The municipality we are focusing on is Uppsala kommun. Our research question concerns how Uppsala kommuns organizational identity maintains and recreates when employees partly work from home. The theoretical framework we apply to this essay is the CCO-perspective based on the Montreal School. We also use the theory of organizational identity and a theory that describes the concept of place. The method to gather data is qualitative semi-structured interviews with six employees at Uppsala kommun. The results show that the employees at Uppsala kommun maintain the organizational identity through the valuebase, sense of belonging to the organization, how they compare Uppsala kommun with other organizations and how they communicate. Furthermore, non-human actors such as place maintain the organizational identity. These places were Teams, the home office and city hall that maintain the organizational identity. Finally, the results show that human and non-human actors recreate the organizational identity through booking meetings, trust, effective work and hybrid solutions. They create different ways of communicating, working and using the digital channels due to distance work. This contributes to society by gaining a greater understanding of how distance work impacts organizational identity. Partly by the importance of an office, but also its effects on coordinating organizations.
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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 | 0.004 | 0.009 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.000 |
| Bibliometrics | 0.002 | 0.003 |
| Science and technology studies | 0.005 | 0.002 |
| Scholarly communication | 0.012 | 0.005 |
| Open science | 0.001 | 0.004 |
| Research integrity | 0.001 | 0.002 |
| Insufficient payload (model declined to judge) | 0.009 | 0.002 |
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".