A Paradox Approach to Organizational Tensions During the Pandemic Crisis
Bibliographic record
Abstract
The COVID-19 pandemic is a massive exogenous shock that reverberated around the world, forcing all types of organizations to change overnight—from the local coffee shop to the international airline. As we try to make sense of the events surrounding the pandemic, one question that has perplexed both scholars and managers alike has been the extent to which this experience is qualitatively different from others. \n \nOne area of research to turn to is research on organizational paradoxes, as the organizational paradox literature has focused extensively on how organizations experience change (e.g., Jay, 2013; Lüscher & Lewis, 2008; Smith & Tracey, 2016). According to the paradox literature, major exogenous change impacts organizations by increasing the saliency of organizational tensions (Smith & Lewis, 2011), such as tensions between exploration and exploitation (e.g., Smith, 2014), cooperation and competition (e.g., Raza-Ullah et al., 2014), or control and collaboration (e.g., Sundaramurthy & Lewis, 2003). The increased salience of tensions is critical for understanding organizations undergoing major change because tensions are both multi-level and multi-faceted, impacting actors ranging from the CEO to the front-line employee (Jarzabkowski et al., 2013) and involving responses that are cognitive (e.g., Miron-Spektor et al., 2018), emotional (e.g., Vince & Broussine, 1996), and material (e.g., Knight & Paroutis, 2017). By focusing attention on the tensions that organizations experience during the pandemic and their responses, the paradox literature can provide shards of clarity to this otherwise incomprehensible event. At the same time, unpacking the pandemic experience through a paradox lens can reveal new insights on organizational tensions, enabling scholars to gain sense of future, seemingly, senseless events.
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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 | 0.008 | 0.013 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.006 | 0.021 |
| Scholarly communication | 0.010 | 0.016 |
| Open science | 0.003 | 0.008 |
| Research integrity | 0.004 | 0.005 |
| Insufficient payload (model declined to judge) | 0.005 | 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".