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Record W991987998 · doi:10.26522/jitp.v20i.3735

LGBT Health Care Access: Considering the Contributions of an Invitational Approach

2022· article· en· W991987998 on OpenAlexaffabout
Judith A. MacDonnell

Bibliographic record

VenueJournal of Invitational Theory and Practice · 2022
Typearticle
Languageen
FieldPsychology
TopicLGBTQ Health, Identity, and Policy
Canadian institutionsYork University
Fundersnot available
KeywordsTransphobiaHeterosexismTransgenderHealth careLesbianHealth equitySociologyGender studiesPsychologyPublic relationsPolitical science

Abstract

fetched live from OpenAlex

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.

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 imitation

Not 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.

metaresearch head score (Codex)0.007
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Theoretical or conceptual · Consensus signal: Theoretical or conceptual
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.448
Threshold uncertainty score0.672

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0070.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.000
Scholarly communication0.0000.001
Open science0.0000.000
Research integrity0.0000.001
Insufficient payload (model declined to judge)0.0000.000

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.

Opus teacher head0.073
GPT teacher head0.476
Teacher spread0.404 · how far apart the two teachers sit on this one work
Validation statusscore_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from it

Classification

machine, unvalidated

Machine predicted; a candidate call from one teacher head, not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designTheoretical or conceptual
Domainnot available
GenreEmpirical

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".

Quick stats

Citations4
Published2022
Admission routes2
Has abstractyes

Explore more

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