Social Perception of Speech in Individuals with Oropharyngeal Reconstruction
Bibliographic record
Abstract
Oral cancer affects approximately 5% of the Canadian population every year. One option for treatment of oropharyngeal cancer includes resection of the diseased tissue with primary reconstruction of the defect using a microvascular free flap, followed by post-operative adjuvant radiation therapy. The aim of reconstructive surgery is to maintain functional speech and swallowing. While the literature provides support for the maintenance of speech intelligibility following reconstructive procedures, certain aspects of resonance may be altered when the palatal structures are involved. Little is known about the effect of such alterations on the perception of speakers who have been treated with microvascular free flap reconstruction. Social perception is a process in which we infer attributes of others, with the speech signal playing an integral part in attribution. The purpose of this study was to explore the social perceptions formed about speakers both before and after surgery for oropharyngeal cancer. The results of this study revealed that positive perceptions of speakers significantly diminished as a result of surgery and negative perceptions increased. Certain variables, such as degree of resection of the soft palate and base of tongue, and sex of the speaker, had influence on the results. This research suggests that intelligibility measurements of speech, although useful, do not provide a complete indication of the social impact of reconstructive surgery on patients with oropharyngeal resections.
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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 | 0.001 | 0.003 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.001 | 0.000 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.001 | 0.000 |
| Open science | 0.000 | 0.001 |
| Research integrity | 0.000 | 0.001 |
| 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 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".