Not All Identifications Are Created Equal: Exploring Employee Accounts for Workgroup, Organizational, and Professional Identification
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
Scholars are increasingly interested in understanding the content and process of employee identification. In this paper, I contribute to this discussion by performing a qualitative case study investigating the accounts employees provide as they make sense of their identification with their workgroup, organization, and profession. Analyses of accounts from 31 members of an architecture firm reveal nine explanations individuals use to make sense of their identifications, which can be categorized using four sensemaking logics: similarity, familiarity, benefits, and investment. The explanations that informants provided differed markedly across targets. Whereas individuals relied heavily on personal relationships, and that their work actually happens in their workgroup in their accounts of workgroup identification, organizational identification was often explained based on the ideology of the organization, the support provided by the organization, the prestige of the organization, and the input the individual had into the organization. In further contrast, accounts of professional identification rested on explanations based in professional archetypes, the enjoyment informants found in their work, and professional norms about the work/life interface. These findings suggest that individuals may construct their identifications differently across targets. I theorize that these patterns are a function of target proximity and the characteristics that distinguish between targets. These findings open up the black box of identification by providing insight into how individuals interpret information about workplace targets. In doing so, the findings illustrate how sensemaking about identification is the result of firsthand experiences with a target in addition to sensegiving.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.002 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.004 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.001 | 0.004 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| 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 it