Queering ways of doing research in MOS with a queer ethos and writing
Bibliographic record
Abstract
Purpose I am responding to the call of this special issue by sharing accounts of my queer activist Ph.D. experience in business schools. It is hoped that this will prompt queered scholarship and research and propose answers to the concerns raised about the discriminatory and rigid nature of the current dominant humanist approach in management organisational studies (MOS). Design/methodology/approach This paper illustrates possibilities that emerge from using a queer ethos, through examples from authors who explored queer theory in MOS before me, queer activists' knowledge and my own experience as a queer troublemaker Ph.D. student doing queered research. I also use metaphors from queer communities to inspire a new way of writing academic research. Findings I articulate two propositions to queer MOS research: (1) how a queer ethos, which is an attitude of openness, provocation and discomfort, can guide and renew research and daily practices in academia, (2) how a queer writing inspired by the queer concept of genderfluidity can help to rethink standards of academic knowledge. Practical implications This queer ethos might help researchers to position themselves between blurry uncertainty and radical closure to develop a much-needed relational, processual and critical way of doing research in MOS. Originality/value Queer alternatives remain in the shadows of MOS. Authors have mostly used the conceptual power of queer theory, but few have explored its empirical dimensions. Queer theory offers still underexplored avenues to destabilize and resignify our way of doing research in MOS by questioning binaries and processes that normalize. I develop this untapped disruptive potential in this paper.
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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 | 0.064 | 0.080 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.003 | 0.002 |
| Science and technology studies | 0.020 | 0.114 |
| Scholarly communication | 0.029 | 0.028 |
| Open science | 0.002 | 0.012 |
| Research integrity | 0.005 | 0.015 |
| Insufficient payload (model declined to judge) | 0.008 | 0.002 |
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".