Values as Metaphor: A Meta-Theoretical Framework of Values in, as, and Through Organizing (WITHDRAWN)
Bibliographic record
Abstract
Values have had a difficult relationship with organizational and management scholarship—one characterized at times by a skewed substance ontology, at other times by a mix of confusion, derision and hype. And yet, values continue to fascinate us. To address these challenges and propose a new foundation for values research, this conceptual paper problematizes the “values” construct and literature in order to introduce four metaphors, based on the literature, that explore archetypical relationships between values and organizing—values-as-biology, values-as-mechanism, values-as-structure, and values-as-interactions—through which to organize the extant literature, circumscribe persistent problems of ontological drift and concept creep, and identify new research avenues. Finally, noting the persistent influence of the dominant social psychology construct proposed following calls to develop an objective “science of values”, I propose a fifth metaphor, values-as-dialectics, which grounds itself in the intersubjectivity and radical temporality of George Herbert Mead in order to propose an alternative, profoundly dynamic way to study values in a spirit of greater plurality.
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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 | 0.007 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.007 | 0.005 |
| Science and technology studies | 0.004 | 0.039 |
| Scholarly communication | 0.010 | 0.018 |
| Open science | 0.002 | 0.004 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.004 | 0.001 |
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".