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Record W2768813904 · doi:10.1080/14681994.2017.1397950

The rise of digisexuality: therapeutic challenges and possibilities

2017· article· en· W2768813904 on OpenAlex

Why this work is in the frame

A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.

affAt least one author lists a Canadian institution in the pinned OpenAlex snapshot.

Bibliographic record

VenueSexual & Relationship Therapy · 2017
Typearticle
Languageen
FieldPsychology
TopicSexuality, Behavior, and Technology
Canadian institutionsUniversity of Manitoba
Fundersnot available
KeywordsFeelingEmerging technologiesEngineering ethicsOrder (exchange)Identity (music)PsychologyEthical issuesWork (physics)Internet privacyPublic relationsSocial psychologyBusinessPolitical scienceComputer scienceEngineering

Abstract

fetched live from OpenAlex

Radical new sexual technologies, which we term “digisexualities,” are here. As these technologies advance, their adoption will grow, and many people may come to identify themselves as “digisexuals” – people whose primary sexual identity comes through the use of technology. Researchers have found that both lay people and clinicians have mixed feelings about digisexualities. Clinicians must be prepared for the challenges and benefits associated with the adoption of such sexual technologies. In order to remain ethical and viable, clinicians need to be prepared to work with clients participating in digisexualities. However, many practitioners are unfamiliar with such technologies, as well as the social, legal, and ethical implications. Guidelines for helping individuals and relational systems make informed choices regarding participation in technology-based activities of any kind, let alone ones of a sexual nature, are few and far between. Thus, a framework for understanding the nature of digisexuality and how to approach it is imperative.

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.

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)0.001
metaresearch head score (Gemma)0.000
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesnone
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.652
Threshold uncertainty score0.748

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0010.002
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.000
Insufficient payload (model declined to judge)0.0000.000

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 head0.183
GPT teacher head0.412
Teacher spread0.229 · 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