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Record W7072128921

Unrelenting: a media-focused political economy analysis of antidepressant use in Canada

2016· dissertation· en· W7072128921 on OpenAlexaffabout

Bibliographic record

VenueMspace (University of Manitoba) · 2016
Typedissertation
Languageen
FieldPsychology
TopicMental Health Treatment and Access
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsNucleofectionGestational periodFusible alloyDiafiltrationTSG101DysgeusiaPretextProteogenomics
DOInot available

Abstract

fetched live from OpenAlex

Although extensive evidence suggests antidepressants are a non-effective treatment for the majority of depressive cases where they are prescribed and despite other developed countries taking steps to provide alternative treatments, Canada's prescription rates continue rising and no state action is being taken. The primary purpose of this study is to explore whether the media in English-speaking Canada, represented by its "newspaper of record," The Globe and Mail, has been performing its essential role in informing Canadians about the controversy surrounding antidepressants and the pharmaceutical system that that has made them central to treating depression. Data was collected in the form of newspaper articles from between 2000 and 2015 in order to analyze media coverage to ensure the essential facts were reported and to qualify to what degree a patient advocacy role challenging the norms of contemporary treatment has been adopted.

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)0.001
metaresearch head score (Gemma)0.005
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: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.043
Threshold uncertainty score0.310

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.005
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0060.011
Science and technology studies0.0040.001
Scholarly communication0.0040.001
Open science0.0010.001
Research integrity0.0010.001
Insufficient payload (model declined to judge)0.0040.000

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 head0.029
GPT teacher head0.269
Teacher spread0.240 · 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
Published2016
Admission routes2
Has abstractyes

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