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Record W2168347725 · doi:10.1177/1049732302238748

To Work or Not to Work: Combination Therapies and HIV

2002· article· en· W2168347725 on OpenAlexaffabout
Eleanor Maticka‐Tyndale, Barry D. Adam, Jeffrey Jerome Cohen

Bibliographic record

VenueQualitative Health Research · 2002
Typearticle
Languageen
FieldMedicine
TopicHIV/AIDS Research and Interventions
Canadian institutionsWindsor Regional HospitalUniversity of Windsor
Fundersnot available
KeywordsGovernment (linguistics)Work (physics)Social workHuman immunodeficiency virus (HIV)MedicinePublic relationsPsychologyPolitical scienceEconomic growthEconomicsFamily medicineEngineering

Abstract

fetched live from OpenAlex

The authors describe the labor force experiences of people living with HIV and AIDS (PHAs) who are taking combination therapies using information from in-depth interviews conducted in 1999 and 2000 in the Windsor and Essex County region of Canada with 35 PHAs. They analyze labor force experience contextually, setting it within the contexts of personal illness experience (including disease trajectory and treatment history), workplace structure and discrimination, the labor market, and the structure of health and social service systems. Barriers to returning to or remaining in the labor force are numerous and require a specific commitment to overcome. Existing workplace and government policies and programs and labor market conditions impede labor force participation for PHAs who have recovered from serious illness and are now able and willing to work.

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)0.002
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 score0.036
Threshold uncertainty score0.072

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0020.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.001
Science and technology studies0.0050.005
Scholarly communication0.0020.001
Open science0.0010.002
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0020.000

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 head0.533
GPT teacher head0.617
Teacher spread0.084 · 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

Citations30
Published2002
Admission routes2
Has abstractyes

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