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Record W3148814396 · doi:10.21203/rs.3.rs-27506/v1

Reporting on the Opioid Crisis (2000-2018) – the Globe and Mail, Canada’s English Language Paper of Record

2020· preprint· en· W3148814396 on OpenAlexaffabout
Amanda My Linh Quan, Lindsay A. Wilson, Kumanan Wilson

Bibliographic record

VenueResearch Square (Research Square) · 2020
Typepreprint
Languageen
FieldMedicine
TopicSubstance Abuse Treatment and Outcomes
Canadian institutionsOttawa Hospital
Fundersnot available
KeywordsGlobeAdvertisingBusinessPolitical scienceMedicine

Abstract

fetched live from OpenAlex

Abstract Objectives: We aim to describe the general characteristics of how Canada’s newspaper of record – The Globe and Mail, reports on opioid-related news, the opioid crisis and its victims,and explore how Canadians’ perceptions of the opioid crisis could have developed over time. Methods: We searched The Globe and Mailbetween 2000 and 2018. We identified all articles related to the keyword “opioids”. Independently and in duplicate, reviewers extracted qualitative data from articles. The Social Representation Theory was used as a framework for understanding the how the opioid crisis is portrayed in Canada. Results: Our search yielded 554 relevant opioid articles.The number of articles peaked in 2009, 2012, and in 2016, coinciding with major developments in the epidemic. The language used in this discourse has evolved over the years and has slowly shifted towards less stigmatizing language. Content analysis of the articles revealed common social representations attributing blame to pharmaceutical companies, physicians, and foreign countries.It is easy to blame these collectives as this contributes to social representations thatare anchored in thepublic’s predisposed notions. Conclusions: Canadian coverage of the opioid crisis is focused on basic social representations and blame patterns towards a few collectives, a shift towards root causes of the opioid epidemic could positively influence the general public’s perception of the opioid crisis and help reap deeper understanding of the issue. Journalists face several obstacles to achieve greater focus and framing of the opioid crisis, a closer working relationshipbetween the media and the research community is needed.

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)0.013
metaresearch head score (Gemma)0.026
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch, Meta-epidemiology (narrow), Research integrity, Insufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.474
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0130.026
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.000
Bibliometrics0.0010.002
Science and technology studies0.0010.001
Scholarly communication0.0000.000
Open science0.0010.002
Research integrity0.0000.006
Insufficient payload (model declined to judge)0.0010.000

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 head0.116
GPT teacher head0.401
Teacher spread0.284 · 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.

Study designNot applicable
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
Published2020
Admission routes2
Has abstractyes

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