Rethinking Historical Methods in Organization Studies: Organizational Source Criticism
Bibliographic record
Abstract
How do we know what we know about an organization’s history? What methodologies do historians use? I explain and adapt the historical method of source criticism for organizational scholars through the new technique of organizational source criticism. Source criticism is how historians do research in archives. The role of source criticism is to identify, analyse and use bias in historical sources to write reliable historical narratives. Organization source criticism emphasizes the plurality of organizational sources. I capture this plurality through the organizational source criticism matrix, which categorizes organizational archival sources into four types based on their category and modality. Category differentiates between narrative and documentary sources, and modality distinguishes reportative from performative sources. The matrix proposes four distinct forms of source criticism for each type of organizational source and exemplifies these through two academic articles from management and organizational history. The paper encourages researchers to adopt organizational source criticism to create robust organizational historical narratives. It also emphasizes the importance of context, triangulation and colligation in organizational historical research. Organizational source criticism is a new historical methodology adapted to researching sources in organizational archives that aims at establishing the veracity and meaning of organizational archival sources. It will benefit organizational scholars who intend to conduct historical organizational archival research.
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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 | 0.187 | 0.293 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.021 | 0.021 |
| Science and technology studies | 0.009 | 0.065 |
| Scholarly communication | 0.029 | 0.048 |
| Open science | 0.006 | 0.014 |
| Research integrity | 0.005 | 0.011 |
| 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".