Voiced inner dialogue as relational reflection-on-action: The case of middle managers in health care
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
We look to the experiences of middle managers in a health-care setting to empirically develop and explore the concept of voiced inner dialogue. Voiced inner dialogue is conceptualised as a form of reflection-on-action whereby fragments of narrative self-reflection reveal an organisation’s unspoken backdrop conversation or interpersonal mush. The normalised intensity that characterises many health-care settings, an artefact of increased governmentality and responsibilisation, leaves middle managers experiencing increased work and personal pressures. The interpersonal mush in this context is centred upon individuals’ felt disconnect between espoused and enacted organisational values. Voiced inner dialogue was triggered in dialogic conversation with the researchers, a type of participant-focused reflexivity. From our qualitative analysis, we present three themes to illuminate how organisational context can inform the creation and maintenance of interpersonal mush, impeding managers’ reflection. Voiced inner dialogue offers an opportunity for managers stuck in the silence of interpersonal mush to engage in reflection-on-action. We conclude with the implications for reflection, reflexivity and management learning.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.001 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.001 | 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 it