“Sorry for Holding You Up”: Surgeons’ Apologies for Lateness in Clinic Settings
Bibliographic record
Abstract
Doctors running late may convey a lack of respect which can impair the therapeutic relationship. This study examines how surgeons address lateness in consultations with patients. We analyzed 52 consultation recordings from a range of surgical specialties in an Australian metropolitan setting. Conversation analysis was used to analyze interactional sequences where lateness was addressed. Six sequences were identified within four recordings. The two consultations with two apologies include a surgeon and registrar apologizing in a neurosurgical consultation and a surgeon apologizing twice within a colorectal consultation. Apologies were either accepted or responded to with an account for not accepting the apology. When these accounts were made, consultations could only progress when patients accepted an explanation for lateness or the degree of complainability about lateness was reduced. The infrequent occurrence of apologies for lateness, and the way in which these sequences unfolded when they did occur, suggest that there is greater acceptability of lateness for surgeons than in ordinary social situations.
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.
How this classification was reachedexpand
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 | 0.002 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.001 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.001 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 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 teacher head, 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".