LGBT Health Care Access: Considering the Contributions of an Invitational Approach
Bibliographic record
Abstract
Lesbian, gay, bisexual and transgender (LGBT) people have historically, and continue today to encounterbarriers to accessing health services. This has been attributed to the well-documented heterosexism,homophobia, biphobia, and transphobia that shape all health and social institutions. In this paper,invitational theory offers insight into the challenges faced by a childbearing lesbian couple to accesssupportive health care, and sheds light on inequities faced by LGBT people when accessing health care inCanada. The author draws on critical feminist research and invitational concepts to build an understandingof four dimensions of this couple’s access to supportive care. The invitational approach is combined withan explicitly critical stance to highlight gender and other relations of power, and to provide a theoreticalrationale for incorporating invitational concepts into equity-related research, including a currentapplication focused on improving LGBT home care access in the Canadian context. Given the deeplyembedded structural inequities that hinder the creation of intentionally inviting environments for diversegroups, this research has implications both for shedding light on areas in need of health care accessresearch, as well as for integrating invitational approaches that align with critical pedagogies into healthcare education.
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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 | 0.027 | 0.028 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.001 |
| Bibliometrics | 0.002 | 0.001 |
| Science and technology studies | 0.021 | 0.046 |
| Scholarly communication | 0.016 | 0.012 |
| Open science | 0.003 | 0.025 |
| Research integrity | 0.008 | 0.011 |
| Insufficient payload (model declined to judge) | 0.009 | 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".