Perceptions and attitudes of McGill dental students towards poverty: a case study
Bibliographic record
Abstract
Context: Evidence shows a strong positive correlation between poverty and numerous adverse health conditions, including oral health diseases.Low-income individuals face barriers in accessing and receiving dental care services due to many causes including tensions in their relationship with dentists.A solution to this problem lies in the training of a new generation of dentists.The education provided in dental school plays a key role in shaping the knowledge, ideas and attitudes of students towards poverty.Objectives: To examine in-depth the perceptions and attitudes of final year dental students at McGill University towards poverty and the dental care provided to low-income patients.Secondary objectives: (i) To explore the extent to which students feel that their education in dentistry has prepared them to work with low-income patients; (ii) To understand if these perceptions shape students' plan for their professional careers.Methodology: A qualitative case study using a participatory approach was performed based on Paulo Freire's theoretical concept of conscientização.The sources of data generation were semi-structured interviews (n=12), participant observation during the outreach program, and document analysis of students' essays and of the website of the McGill Faculty of Dentistry.A deductive-inductive thematic analysis strategy was used to analyze the data.Results: Dental students exhibited incipient conscientização about poverty-related themes; they perceived poverty as a distant subject, and as a responsibility of the government or of the poor individual themselves.They judged Canada's dental health system as unfair to people living in poverty, but admitted having a lack of knowledge of dental services especially those offered in the welfare program, and were unable to propose strategies to ameliorate it.Students identified several challenges with respect to the McGill Dentistry outreach program including lack of continuity and comprehensiveness of care, as well as deficient compliance with clinical guidelines.Students did not present concrete plans to work with low-income communities in the future.
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 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 | 0.002 | 0.003 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.001 |
| Bibliometrics | 0.002 | 0.002 |
| Science and technology studies | 0.017 | 0.005 |
| Scholarly communication | 0.003 | 0.001 |
| Open science | 0.002 | 0.006 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.005 | 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".