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Record W42685190

The landscape of rules governing access to personal information for health research: a view from afar.

2003· article· en· W42685190 on OpenAlexaffabout
Patricia Kosseim

Bibliographic record

VenuePubMed · 2003
Typearticle
Languageen
FieldMedicine
TopicEthics in Clinical Research
Canadian institutionsCanadian Institutes of Health Research
Fundersnot available
KeywordsMeaning (existential)Set (abstract data type)Public relationsOrder (exchange)Context (archaeology)Process (computing)Internet privacySociologyPolitical scienceBusinessLaw and economicsPsychologyComputer science
DOInot available

Abstract

fetched live from OpenAlex

What is asked, or should be asked, of the law student is not that he learn, by heart, and in all their detail, all the rules in force during his time as student: that will be of little service to him in his later professional life when many of those rules will have changed. Of far greater importance to the student will be a knowledge of the structure within which the rules and concepts are organized, the meaning of these categories and concepts, and the relationship of the rules among themselves. The legislators may, indeed, with a stroke of the pen modify the actual legal rules, but these other elements and features nonetheless subsist. They cannot be so arbitrarily changed because they are intimately linked to our civilization and ways of thinking. The legislators can have no more effect on them than upon our language or our reasoning process. (1) Introduction How can we uphold the individual right of privacy in respect of personal information, while also allow necessary access to that information for bona fide health research in order to improve the health of Canadians and their health services? How can we develop a coherent set of norms that respects Canadians' values and strikes a socially acceptable balance between them? How can we ensure that these norms are workable in practice and sufficiently compatible to govern transfers of data across different jurisdictions and/or sectors of activity? Such has been identified as one of the major public policy challenges in the current context of health care reform. The Senate Standing Committee on Social Affairs, Science and Technology recently described the challenge as follows: The right to privacy and confidentiality of personal health information is a very important value for Canadians. Now more than ever, Canadians need reassurance that their privacy and confidentiality will be respected in this era of rapidly advancing technology. However, the quality of their health and health care is also a value that Canadians cherish very dearly. Health care providers, health care managers and health researchers need access to personal health information to improve the health of Canadians, strengthen health services and sustain a high quality health care system. The present challenge for Canadians is to set acceptable limits around the right to privacy, on the one hand, and the need for access to information (by health care providers, managers and researchers) on the other, in order to achieve an appropriate balance between them. (2) Similarly, Commissioner Roy J. Romanow Q.C. echoed these concerns when he articulated the challenge in these terms: Some might wonder why a chapter on information would figure so prominently and be placed at the beginning of a report on the future of Canada's health care system. The answer is that leading-edge information, technology assessment and research are essential foundations for all of the reforms outlined in subsequent chapters of this report. Furthermore, health research--especially biomedical and scientific research--is an increasingly important component of Canada's knowledge economy and a source of high-skilled, well-paid employment for thousands of Canadians ... With better information management and technology in place, researchers can assess the impact and value of different treatments and approaches to delivering health care services in addition to developing and testing new discoveries and cures ... Researchers and policy-makers would have access to aggregate data compiled through the electronic health record system. These data could be extracted generically for health research purposes, without being linked to any individual electronic health record. The Commission understands that researchers would, in many cases, prefer to have access to person-oriented health information to allow them to track certain illnesses or health-related factors over time. …

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)0.075
metaresearch head score (Gemma)0.058
Version: metacan-v3-hybrid-931329e0061cValidation status: machine_predicted_unvalidated
Candidate categoriesMetaresearch
Consensus categoriesnone
DomainCandidate signal: Methods · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: none
Teacher disagreement score0.925
Threshold uncertainty score0.832

Distilled classifier scores by category (both heads)

CategoryCodexGemma
Metaresearch0.0750.058
Meta-epidemiology (narrow)0.0010.002
Meta-epidemiology (broad)0.0010.002
Bibliometrics0.0030.005
Science and technology studies0.0320.133
Scholarly communication0.0500.028
Open science0.0050.011
Research integrity0.0330.036
Insufficient payload (model declined to judge)0.0050.002

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 head0.712
GPT teacher head0.590
Teacher spread0.122 · 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 designObservational
DomainMethods
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

Citations2
Published2003
Admission routes2
Has abstractyes

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