Multi‐Temporality and the Ghostly: How Communing with Times Past Informs Organizational Futures
Bibliographic record
Abstract
Abstract Despite growing interest in time, history, and memory, we lack an understanding of the multi‐temporal reality of organizations – how past, present, and future intersect to inform organizational life. In assuming that legacies are bequeathed from past to present, there has been little theorization on how this works practically. We propose that the lexicon of the ghostly can help. We contribute a theory of ghostly influence from past to future by offering a framework focusing on core moments of organizational existence: foundation, strategic change, and longevity commemoration, and illustrate this using a case study of consumer goods multinational Procter & Gamble (1930–2010). In showing that organizational ghosts, absent members whose presence is consequential to the actions of living members, are active and dialogical, we illuminate a dialectical interaction missing from other non‐linear conceptions of temporality. This emphasizes the performative force of a dynamic past that provides an inference to action in the present and future.
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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 | 0.026 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.004 | 0.017 |
| Scholarly communication | 0.008 | 0.014 |
| Open science | 0.001 | 0.006 |
| Research integrity | 0.001 | 0.002 |
| 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".