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Record W7008719926

A client focused abortion health centre: creating a sense of comfort and security through the built environment

2019· dissertation· en· W7008719926 on OpenAlexaboutno aff

Bibliographic record

VenueMspace (University of Manitoba) · 2019
Typedissertation
Languageen
FieldMedicine
TopicReproductive Health and Contraception
Canadian institutionsnot available
Fundersnot available
KeywordsPracticumAbortionAnxietyBuilt environmentHealth care
DOInot available

Abstract

fetched live from OpenAlex

Despite political advancements surrounded by abortion rights, issues of comfort and anxiety within abortion provider facilities still remain. Those who undergo an abortion may be faced with difficult situations that can place them in a vulnerable and emotional position. The intent of this practicum was to highlight the issues faced by both clients, and healthcare providers involved with abortion provider facilities, and address these challenges through design interventions. This practicum took into account issues of safety, comfort, and anxiety through a combination of theoretical literature, design precedents, and programming. Concepts that informed this practicum include supportive design theory and positive distractions explored by theorist Roger Ulrich, environmental comfort, and security techniques. This design practicum proposes a client-focused abortion health centre for the city of Winnipeg, Manitoba, Canada, aiming to support the emotional and physical well-being of the users in the facility.

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 imitation

Not 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.

metaresearch head score (Codex)0.004
metaresearch head score (Gemma)0.003
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.015
Threshold uncertainty score0.037

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0040.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0010.001
Science and technology studies0.0090.010
Scholarly communication0.0050.002
Open science0.0020.007
Research integrity0.0020.003
Insufficient payload (model declined to judge)0.0050.001

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 head0.016
GPT teacher head0.248
Teacher spread0.232 · 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 source (direct Gemma or distilled Codex), not a consensus.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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

Citations0
Published2019
Admission routes1
Has abstractyes

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