<i>Hiding in plain sight</i> : Exploring the complex pathways between tactical concealment and relational wellbeing
Bibliographic record
Abstract
We argue that the current environment in higher education is one of the primary drivers for the widespread adoption of concealment tactics with the aim of enhancing wellbeing. To explore the relationship between concealment and wellbeing, we draw upon Scott’s conceptualization of “hidden transcripts” and Keyes’s five dimensions of social wellbeing. Using a collaborative ethnographic approach, we examine a 2-year period of individual and collective inquiry by an eclectic multidisciplinary, international group of academics. Our empirical and theoretical contributions expose a complex and, at times, seemingly contradictory relationship between tactical concealments and relational wellbeing, with variously generative and destructive pathways between them. Our research offers a lens through which we can critically explore and extend our understanding of alternative pathways to wellbeing in organizational life.
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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 | 0.006 | 0.007 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.005 | 0.024 |
| Scholarly communication | 0.008 | 0.010 |
| Open science | 0.001 | 0.009 |
| Research integrity | 0.002 | 0.003 |
| 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".