Notice bibliographique
Résumé
For much of nursing's history, we were safe to assume that our scholarly knowledge development was taking us slowly and certainly toward increasingly unassailable truths—claims we could confidently assert as core nursing knowledge and evidence for practice. But we did not really anticipate the form of social upheaval that seems to have landed upon us in the last decade or so. “Post-truth” has only recently entered our lexicon (D'Ancona 2017; Oxford Dictionaries 2016), and its prominence in the public press and scholarly discourse clearly signals the degree to which we are worried. Science seems to have lost its grip on collective imagination as something that we can rely on for being solidly grounded in systematic processes toward logical progression of testable claims; it is now something that everyone has access to through their “own research” on search engines that themselves are governed by machine learning, persuasion, and conspiracy theorizing. As Perry points out, “While scientists labour to fact-check, posttruth rolls on, swamping the media and morphing the message” (Perry 2017, 1). The centre of gravity in terms of what does and does not constitute a truth claim in our discipline is slipping sideways in a manner that feels increasingly uncontrollable and at times outright dangerous. What is it that nursing ought to be doing about this? Do we cling to our conventional ways of evidence-building, theorizing, and philosophizing and hope that the world order begins to self-correct before it topples into chaos? Or do we try to join in the whirling dervish of post-truth certainty claims and give up on the illusion of a coherent and articulable disciplinary integrity? I suspect that many of us are feeling quite helpless and discouraged, hanging onto a conviction that truth in nursing really does matter but not knowing how to protect it from the onslaught of misinformation, challenges to the conventional social order, and political positioning that we see all around us. I wish I could manufacture a straightforward, accessible, incontestable response to all of this, but I cannot. Instead, I want to invite a collective community dialogue among those of us who truly care about the future of this discipline (and we are many!) to galvanize our efforts around those former “truths” that we are at most risk for losing, and to stand together in defense of the ramparts as we hang on to that which we value. Perhaps the most prominent among these misinformations for our discipline has been the rampant “anti-vax” movement that arose in the midst of the COVID-19 pandemic. Since vaccines were first explored (The World Health Organization tells us that was in the 15th century, although rudimentary attempts to expose people to disease vectors as a means of preventing illness may have begun many centuries earlier) (World Health Organization 2025), the recognition that prevention was better than cure has been pervasive. Since its inception as a formalized professional practice in the 1800s, nursing has been solidly supportive of public health and preventative intervention. We have been at the forefront of most vaccination campaigns, providing that trusted voice to an anxious public, assuring it that we understand and respect the science, that it is safer to be inoculated than to risk the effects of these diseases. And because of that consistency of purpose and confidence in the integrity of science, we have continued to maintain the high trust of the public over all the years in which such things have been recorded (Roush 2025). The complexity of the challenge nursing faced during the pandemic shocked many nurses to the core. The manner in which they were treated within their workplaces and in the public domain led some nurses to question their commitment to the profession and even actively participate in the spreading of misinformation (Grace 2021). Stewart (2022) wondered if these conditions had caused some of her nursing colleagues to move “beyond professional frustration to a betrayal of our shared humanity” (p. 419), including abandoning their long-held convictions about truth and evidence. As she wrote, “Without answers and absolutes, we all need help to live this day, and then the next” (p. 419). Tieu et al. (2023) reflect on the impact of this post-truth era for the field of knowledge translation, positioning that field as a highly complex sociological challenge. Those involved in this work “…may recognise scientific evidence as provisional, contested, and existing alongside many other views that should be afforded equal consideration, but such recognition does not entail that they regard all viewpoints as having the same epistemic status” (Tieu et al. 2023, 5). This seems an important perspective for nursing to align itself with, as translating that which we know as a discipline into the context of everyday cases and contexts is a major component of nursing work. It seems to me that, as a discipline, we have spent considerable effort over recent decades challenging ourselves with respect to the ideas we stand firm with and those we consider subject to healthy critique and challenge. Nursing Inquiry has played a major role in showcasing the best of that critique, focusing on the realities of our profession that an equity and inclusion lens illuminate. Nurses and nursing scholars have worked hard to redress some of what we have come to understand as fundamental societal imbalances and injustices that we either did not see or did not know how to act upon in an earlier era. I am thinking about systemic and structural racism, the gender binary, and a whole range of cultural safety infractions in this regard. We have welcomed these challenges to our previous strongly held “truths” because we understand them as consistent with our wider social mandate and commitment as a profession to care for all persons in need of our care. But perhaps some of these shifting sands of what counts as a certainty have contributed to disrupting our capacity to stand firmly on the foundation of our disciplinary knowledge. I would argue, as would our nursing professional associations (e.g., American Nurses Association 2024; Guest and Villeneuve 2021) that, even as we support a wide latitude of perspective on what is wrong with the world and our profession, we still have a fundamental need to distinguish truths from lies. As political sociologist Silke van Dyk wrote, “Critique in the best sense of the word involves not accepting facts as given or necessary. But this critique – and this is certainly a challenge for the de-constructivist paradigms of criticism – should lead towards facts and figures rather than away from them” (van Dyk 2022, 47). Just because an idea resonates with an individual nurse's sense of “personal knowing” does not necessarily render it legitimate (Thorne 2020). In these complicated times, it seems urgent that we find ways to come together in all of our various nursing communities to reflect on, wrestle with, and reaffirm who we are, what it is that we know, and how we know it. Naturally, as van Dyk's words remind us, we must “highlight those cases in which we may no longer recognize the lie because it is so deeply inscribed in conventions and systems of thought” (p. 47). But in this delicate post-truth moment, it may also be time to permit some of our critical focus to shift beyond our widely vocal critique of ourselves (our history, our practices, and our shortcomings in terms of an ideal future for all), so that we can allow space for reconfirming the disciplinary nursing certainties that will prepare us for this complex and uncertain future. Disciplinary truths may turn out to be a useful “counterbalance to those powerful social, cultural, political and market forces that are able to challenge scientific evidence and promote disinformation to the detriment of democratic outcomes and the public good” (Tieu et al. 2023, 1). And lest I sound old-school in advocating an uncritical return to our conventional roots, I am also confident that we don't have to lose sight of the optimistic vision best captured by a newer generation of nursing thought leaders who remind us that we don't need to wallow in “our dystopian present” to be capable of “reimagining a radical future” (Blaine Brown et al. 2022). As with all crises, perhaps this one does come with intriguing opportunities.
Récupéré en direct depuis OpenAlex et désinversé. Les résumés ne sont pas conservés dans cette base de données : les index inversés représentent 8,6 Go des 9,3 Go de texte de la base, et le serveur dispose de 13 Go libres.
Comment cette classification a été obtenuedéplier
Prédiction distillée sur la base complète
Imitation des enseignantsNi prévalence calibrée, ni vérité terrain. Validation humaine à venir. Apprise à partir de 10 348 étiquettes directes de Codex et de 10 348 étiquettes directes de Gemma. Le mode candidate est l'union des têtes enseignantes seuillées; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont ni des étiquettes humaines ni des étiquettes directes de modèles de pointe.
Scores Codex et Gemma par catégorie
| Catégorie | Codex | Gemma |
|---|---|---|
| Métarecherche | 0,001 | 0,000 |
| Méta-épidémiologie (sens strict) | 0,000 | 0,000 |
| Méta-épidémiologie (sens large) | 0,000 | 0,000 |
| Bibliométrie | 0,000 | 0,001 |
| Études des sciences et des technologies | 0,001 | 0,001 |
| Communication savante | 0,000 | 0,001 |
| Science ouverte | 0,000 | 0,000 |
| Intégrité de la recherche | 0,000 | 0,001 |
| Charge utile insuffisante (le modèle a refusé de juger) | 0,000 | 0,000 |
Scores machine (provisoires)
Les deux têtes enseignantes du modèle étudiant, lues sur ce travail. Un score ordonne la base pour la relecture; il n'affirme jamais une catégorie, et le statut de validation accompagne chaque rangée tel quel.
Scores de référence d'un modèle non mature (critères de maturité non atteints, 7 itérations). Un score ordonne; il n'affirme jamais une catégorie.
score_only:v0-immature-baseline · tel quel depuis la passe de notation : score_only signifie que le nombre peut ordonner les travaux, et qu'aucune étiquette de catégorie n'en découleClassification
machine, non validéePrédiction automatique; un appel candidat d’une seule tête enseignante, pas un consensus.
Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».