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Record W2579583215 · doi:10.1007/s12152-016-9293-4

Addiction and the Brain: Development, Not Disease

2017· article· en· W2579583215 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

VenueNeuroethics · 2017
Typearticle
Languageen
FieldNeuroscience
TopicNeurotransmitter Receptor Influence on Behavior
Canadian institutionsUniversity of TorontoCanada Research Chairs
FundersRadboud Universiteit
KeywordsAddictionBrain diseaseDiseaseNeuropsychologyPsychologyPsychiatryMedicineNeuroscienceCognitionPathology

Abstract

fetched live from OpenAlex

I review the brain disease model of addiction promoted by medical, scientific, and clinical authorities in the US and elsewhere. I then show that the disease model is flawed because brain changes in addiction are similar to those generally observed when recurrent, highly motivated goal seeking results in the development of deep habits, Pavlovian learning, and prefrontal disengagement. This analysis relies on concepts of self-organization, neuroplasticity, personality development, and delay discounting. It also highlights neural and behavioral parallels between substance addictions, behavioral addictions, normative compulsive behaviors, and falling in love. I note that the short duration of addictive rewards leads to negative emotions that accelerate the learning cycle, but cortical reconfiguration in recovery should also inform our understanding of addiction. I end by showing that the ethos of the disease model makes it difficult to reconcile with a developmental-learning orientation.

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)0.000
metaresearch head score (Gemma)0.003
Version: codex-gemma-dda1882f352aValidation status: machine_predicted_unvalidated
Candidate categoriesScience and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Bench or experimental · Consensus signal: none
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.373
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0000.003
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.000
Science and technology studies0.0020.001
Scholarly communication0.0000.000
Open science0.0010.000
Research integrity0.0000.001
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 head0.089
GPT teacher head0.333
Teacher spread0.244 · 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