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BackPage Online, August 2019

2019· article· en· W4244114477 on OpenAlexfundno aff

Bibliographic record

VenueThe Back Letter · 2019
Typearticle
Languageen
FieldSocial Sciences
TopicLegal case studies and regulations
Canadian institutionsnot available
FundersYork UniversityWorld Health Organization
KeywordsComputer scienceInternet privacy

Abstract

fetched live from OpenAlex

Is the WHO Choosing Profits For Big Pharma Over Human Lives? The World Health Organization (WHO) has the reputation of being a dependable proponent of good health and evidence-based medical care. However, the WHO fell down on the job when it came to the opioid overuse and addiction epidemic. According to a recent US Congressional investigation by representatives Katherine Clark (Democrat from Massachusetts) and Hal Rogers (Republican from Kentucky), the WHO allowed itself to become a conduit for inaccurate claims about opioid risks and benefits—and to become a marketing arm for Purdue Pharma and other opioid developers. And they suspect that these WHO's promotional efforts will lead to a replication of the deadly US opioid crisis in other parts of the world. “We hope the WHO will no longer allow the same companies and the same people who recklessly chose profits over human lives in the United States to inflict the opioid crisis on the rest of the world,” according to Clark and Rogers. In an article at BMJ, Purdue Pharma asserted that the Congressional report “seeks to vilify the company through baseless allegations.” A WHO spokesman said that the agency is reviewing the report point by point. Here is a link to the full Congressional report: https://katherineclark.house.gov/_cache/files/a/a/aaa7536a-6db3-4192-b943-364e7c599d10/818172D42793504DD9DFE64B77A77C0E.5.22.19-who-purdue-report-final.pdf Here is a link to the BMJ article on the report: www.bmj.com/content/365/bmj.l2343.full US Healthcare System Seeking Cost Savings by Exploiting a Key Group of Workers? Burnout has become a huge issue among healthcare providers in the United States and other affluent nations. It diminishes the futures of patients and providers alike—and is costing society a small fortune, as many healthcare providers are dropping out of the practice of medicine altogether. According to a recent article by internist Danielle Ofri, MD, of Bellevue Hospital in New York, the corporate healthcare system is attempting further cost savings by taking advantage of the professionalism and ethics of doctors and nurses—and manipulating them to work endlessly. “By now, corporate medicine has milked just about all the ‘efficiency’ it can out of the system. With mergers and streamlining, it has pushed the productivity numbers about as far as they can go. But one resource that seems endless—and free—is the professional ethic of medical staff members,” according to Ofri. This is bad business and bad medicine. Here is a link to the full article at the New York Times: www.nytimes.com/2019/06/08/opinion/sunday/hospitals-doctors-nurses-burnout.html?action=click&module=Opinion&pgtype=Homepage Has the Healthcare System Lost Sight of “Healing” as Its Main Priority? A recent article at the Harvard Business Review makes a compelling argument that the medical system has lost sight of a key priority: “healing.” “Health care plays a unique and sacred role in society—to provide healing—and it is up to its leaders to reclaim the primacy of this role before it is too late. Healing requires more than medication and technology directed toward physiological improvement. Emotional and spiritual rehabilitation matter, too,” according to critical care specialist Rana L. A. Awdish, MD, and health services researcher Leonard Berry. “Clinicians who work to understand the complex emotions that diagnosis and treatment evoke—and then show kindness to patients as they face those challenges—can mitigate some of the suffering that illness confers. Kindness helps to heal not just the recipient, but also the giver. Kindness can be learned, and that starts by embedding it in organizational culture, just as protocols for the safe administration of medications are embedded.” Here is a link to their powerful argument that medicine has gone astray and needs to keep its eyes on the most important priority: https://hbr.org/2019/05/putting-healing-back-at-the-center-of-health-care

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)0.004
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesInsufficient payload (model declined to judge)
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Not applicable · Consensus signal: Not applicable
GenreCandidate signal: Other · Consensus signal: Other
Teacher disagreement score0.934
Threshold uncertainty score0.094

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0010.004
Meta-epidemiology (narrow)0.0010.000
Meta-epidemiology (broad)0.0010.001
Bibliometrics0.0020.001
Science and technology studies0.0020.000
Scholarly communication0.0070.003
Open science0.0010.003
Research integrity0.0020.002
Insufficient payload (model declined to judge)0.9340.919

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 head0.017
GPT teacher head0.280
Teacher spread0.262 · 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.

Study designNot applicable
Domainnot available
GenreOther

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".

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Citations0
Published2019
Admission routes1
Has abstractyes

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