Horizontal and vertical communication as determinants of professional and organisational identification
Bibliographic record
Abstract
Purpose This paper aims to present the results of a study into the relationship between horizontal and vertical communication and professional and organisational identification. Design/methodology/approach An empirical study was carried out at a large hospital in The Netherlands with multiple locations. Hospital employees ( n = 347) completed a written questionnaire. Findings The results show that although employees identify more strongly with their profession than with their organisation, there is a positive connection between professional and organisational identification. Dimensions of vertical communication are important predictors of organisational identification, whereas dimensions of horizontal communication are important predictors of professional identification. Research limitations/ implications Identification with the overall organisation does not depend primarily on the quality of contact with immediate colleagues within a work group or department; rather, it depends more on appreciation of the communication from and with the organisation's top management. Practical implications Management should find a balance between communication about organisational goals and individual needs, which is crucial in influencing professional and organisational identification. Originality/value Previous research has shown a positive link between the communication climate at a specific organisational level and the employee's identification with that level. The current study adds to this concept the influence of horizontal and vertical dimensions of communication on identification among different types of employees.
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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 | 0.037 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.002 | 0.001 |
| Open science | 0.000 | 0.002 |
| Research integrity | 0.000 | 0.001 |
| Insufficient payload (model declined to judge) | 0.004 | 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".