The maladaptive threats of identity limbo and cohesion resistance: A qualitative case study examining the challenges of over-inclusion and status and dominance confusion
Bibliographic record
Abstract
This doctoral thesis examines the construct of organizational identity of knowledge workers involved in a merger or acquisition, to gain insights into the complex social-behavioural responses of participants to perceptions of imposed integration of social groups. Following a qualitative case study methodology, this study used observation and interview data collection to capture the authentic experiences of participants from the host firm, and from the two acquired groups. The central curiosity guiding this study asked if continuity in subordinate identities, that transition relatively seamlessly from acquired to host organizations, offers the same adaptive or insulating effect against identity threat as superordinate identification. The central thesis proposed that despite the relative consistency between subgroup identities, the involuntary introduction of new members into a work team would continue to arouse perceptions of identity threat and provoke associated efforts to resist assimilation through withholding cohesion-building behaviours.\n\nThe data were analysed using Atlas-ti to draw out key themes and patterns. The results suggested a relationship between the different integration strategies applied to the two acquisitions, and the participants’ perceptions of the integration. The data also suggested a relationship between levels of identity and reluctance to extend and engage in cohesion-building behaviours among host and adopted participants. Serendipitous findings pointed to potential triggers for the identity-related resistance, that most notably included status and dominance confusion that interfered with perceptions of identity continuity, and resistance to over-inclusion in superordinate and principle identities that lacked salience and distinctiveness.\n\nThis paper introduced two new concepts to the field of identity research, including principle identity, and resistance to cohesion building behaviors. This paper also examined the perspectives of knowledge workers, as a distinctive cohort, to gain some insights into if and how a merger of like-professionals is experienced uniquely. Finally, the qualitative case study methodology offered an opportunity to examine the macro-economic contexts of the two acquisitions for relevance, and these contexts were found to be significant to a holistic understanding of the experiences of the integrations.
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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 | 0.018 | 0.020 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.017 | 0.014 |
| Scholarly communication | 0.005 | 0.005 |
| Open science | 0.003 | 0.007 |
| Research integrity | 0.003 | 0.004 |
| Insufficient payload (model declined to judge) | 0.002 | 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".