MétaCan
Menu
Back to cohort
Record W4412825385 · doi:10.1097/jfn.0000000000000554

Like a Rolling Stone: Confronting Privilege and Power in the Fight Against Trafficking

2025· article· en· W4412825385 on OpenAlexaboutno aff
Carolyn M. Porta, Donna Scott Tilley

Bibliographic record

VenueJournal of Forensic Nursing · 2025
Typearticle
Languageen
FieldSocial Sciences
TopicSex work and related issues
Canadian institutionsnot available
Fundersnot available
KeywordsPrivilege (computing)Power (physics)Forensic nursingPoison controlSuicide preventionInjury preventionHuman factors and ergonomicsComputer securityCriminologySociologyPolitical scienceMedical emergencyMedicineComputer science

Abstract

fetched live from OpenAlex

“Ahh you’ve gone to the finest schools, alright Miss Lonely, But you know you only used to get juiced in it. Nobody’s ever taught you how to live out on the street, and now you’re gonna have to get used to it. How does it feel, how does it feel? To be on your own, with no direction home. Like a complete unknown, like a rolling stone” (Dylan, 1965). Let us be clear. Far too many people are trafficked and far too few traffickers or buyers are caught, found guilty, or punished. An estimated 27 million people live in modern slavery worldwide, with 12 million of them being children (U.S. Department of State, 2024). In the United States (U.S.), sex trafficking is the most common type of trafficking (U.S. Department of State, 2024), disproportionately involving Black girls (Congressional Black Caucus Foundation, 2020). Since 2019, between 202 and 289 federal human trafficking cases were filed annually. Nearly all of the 2023 cases (98%) filed were sex trafficking (versus forced labor trafficking; caveat: the feds tend to focus more heavily on sex trafficking); the cases involved 638 victims aged 4–21 (average age 15) who were predominantly female and U.S. citizens, and had been recruited via social media tools including Snapchat and Facebook (Human Trafficking Institute, 2024a; U.S. Department of State, 2024). Despite a 96% conviction rate, a mere 10 traffickers were convicted to life sentences in 2023 (Human Trafficking Institute, 2024b). With so many children and women trafficked and so few networks, traffickers, and sex buyers stopped [see long overdue recent court cases involving Canadian billionaire Robert Miller (Banerjee, 2025) and American Michael Jeffries, former Abercrombie & Fitch CEO (U.S. Department of Justice, 2024)], every sense of danger, injustice, disgust, and intolerance should be heightened. The JFN editorial board commissioned this special issue on trafficking with earnest pursuit of solutions and intentional avoidance of restating the problem. You will read compelling and inspiring articles offering strategies, tools, and cautions which will strengthen your forensic nursing care for the trafficked. Absorb these shared best practices, test them in your settings, communicate back your lessons learned, and contribute to producing tangible tactics that work. In August 2025, the International Association of Forensic Nurses annual conference will convene in Omaha, Nebraska. As you prepare to learn, network, and grow, consider taking a deep and dark dive into how one national child-trafficking network was disrupted when the Franklin Federal Credit Union was investigated (Nickel, 2012). While we forensic nurses fight sex trafficking via our direct care for those who survive, we must do so with eyes wide open, recognizing the complex, historic, and present-day webs of money, power, politics, and addictions in which trafficking occurs. And when we do let ourselves see what can’t be unseen, rather than be lost in discouragement or a sense of powerlessness, we should stand resolute in doing what is in our control, just as American musician Bob Dylan did in using his lyrics to fight injustice (Hurricane), protest war (Masters of War), challenge privilege (Like a Rolling Stone), and many more. Like Bob Dylan hauntingly describes, today we might be the privileged, the ones untouched by the tangible pain of losing a loved one to human trafficking, of someone missing or murdered. On another day, we might be the ones grieving a lost loved one, or experiencing the pain of their unknown status. We write this editorial with determination to never be those privileged people who, in day-to-day living, ignore or miss signs of trafficking. And while we try not to overindulge our hypervigilance, a symptom of secondary traumas from being forensic nurses, we should, no, we must, lean into the heightened awareness and intuition our hypervigilance fuels to recognize harms or threats in our proximities, and to help others do the same in theirs. This means, for example and for starters, we can’t get lost in our own priorities, letting our lists of to-dos draw attention away from what might be happening around us, locally and globally. We, like you, and like all who, at times, hold positions of care, of authority, of privilege, and of freedom, must live our intolerance of trafficking and of injustices with explicit antitrafficking, bold, and defiant hearts, minds, voices, and actions.

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)0.001
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: Qualitative · Consensus signal: Qualitative
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.424
Threshold uncertainty score0.319

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 studies0.0000.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.010
GPT teacher head0.300
Teacher spread0.290 · 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.

The models applied no category: nothing in the taxonomy fit this work.
Study designQualitative
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
Published2025
Admission routes1
Has abstractyes

Explore more

Same venueJournal of Forensic NursingSame topicSex work and related issuesFrench-language works237,207