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Feeding Your Fire (Without Burning Out)

2012· article· en· W7000515466 sur OpenAlexaboutno aff

Notice bibliographique

RevueWBI Studies Repository · 2012
Typearticle
Langueen
DomaineHealth Professions
ThématiqueVeterinary Practice and Education Studies
Établissements canadiensnon disponible
Organismes subventionnairesnon disponible
Mots-clésSession (web analytics)Work (physics)WelfareCompassion fatigueCompassionStaffing
DOInon disponible

Résumé

récupéré en direct d'OpenAlex

I was on a call to help a dog that was hit by a car, and I showed up and it was a sheltie," he says."And I've owned shelties all my life, and immediately I saw my dog on the side of the road, dead."Abi-Hassan, executive director of the Halifax Humane Society in Daytona Beach, Fla., who teaches workshops on stress management and compassion fatigue issues, says it was one of many moments that showed how much he and other animal welfare workers need to develop the emotional skills to survive."It really took me back and made me realize that what I need to take care of is me," he says, "because if I don't take care of myself, I'm not going to be around to take care of these animals."It makes sense, and yet … animals need so much, and so many of them are suffering.And whether you work hands-on in the field or in the shelter, in your home as a foster caregiver, or in an office on policy issues that can help animals on a national level, what needs to be done can seem endless.In a recent employee feedback session at The HSUS, staffers were asked to share ideas about how to make their work environment better.A huge sheet of paper was pinned to a wall, and employees sounded off about ongoing challenges, offering suggestions and commenting on each other's thoughts.In one spot, someone wrote: "People feel like they have to be on the job 24/7/365!There needs to be more work-life balance."Next to that, someone had retorted: "Animal cruelty doesn't end at 5 o'clock."Others had chimed in on each side, drawing arrows and plus signs and saying, "Exactly!"It's a debate many animal welfare advocates have regularly, among each other and within themselves.The suffering we confront is so great it seems to demand all of our hearts.Yet if we give all of our hearts, what's left of us to keep giving?Advocates working for major societal change frequently wrestle with the implications of psychiatrist and Holocaust survivor Viktor Frankl's credo: What is to give light must endure burning.Many accept that sacrifice to a greater cause.But how can we keep our fires lit without burning out, take the time to refuel, and find the "kindling" we need to stay healthy?In the standoff between I-have-to-help-more-animals and I-need-some-space-to-breathe, some people never figure out the answer.Some figure it out-and change jobs.And some manage to find a balance that works. A Field That Eats its YoungFor those who have good coping skills, healthy boundaries, or natural resilience, animal welfare work can be stressful, but is usually manageable.But even the most mentally flexible folks can get overloaded.And for others, coping with endless animals and people in need, repeatedly bearing witness to their suffering, and knowing that not all of them can be helped can bring on compassion fatigue, a kind of secondary post-traumatic stress disorder caused by exposure to the pain of others.It's a problem common among people who treat and respond to those who've been directly impacted by violence or other types of trauma-injuries, sickness, loss of home and family, all the things that shelter and rescue workers see daily in the animals they help.When caregivers don't give themselves enough care, it can threaten the work they pursue so passionately.One burned-out animal advocate who spent years trying to keep animals out of shelters so they wouldn't be euthanized speaks of reaching a point where, to her horror, she just didn't careIt was a moment that Miguel Abi-Hassan will never forget: CARE ABOUT CATS?HUMANESOCIETY.ORG/ABOUT/DEPARTMENTS/HSISP/ 27

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 machine sur la base complète

Imitation des enseignants

Ni prévalence calibrée, ni vérité terrain. Validation humaine à venir. Le volet Gemma est une étiquette directe du modèle pour chaque travail de la base, lue sur la notice réduite au titre. Le volet Codex est un classifieur appris des 10 348 étiquettes directes de Codex et calibré sur les taux pondérés de l'échantillon; les champs sans appui suffisant ne portent aucun appel Codex. Le mode candidate est l'union des deux volets; le consensus est leur intersection. Ces sorties portent le statut machine_predicted_unvalidated et ne sont pas des étiquettes humaines.

score de la tête « metaresearch » (Codex)0,001
score de la tête « metaresearch » (Gemma)0,004
Version: metacan-v3-hybrid-931329e0061cStatut de validation: machine_predicted_unvalidated
Catégories candidatesaucune
Catégories consensuellesaucune
DomaineSignal candidat: aucune · Signal consensuel: aucune
Devis d'étudeSignal candidat: Sans objet · Signal consensuel: Sans objet
GenreSignal candidat: Autre · Signal consensuel: Autre
Score de désaccord entre enseignants0,279
Score d'incertitude au seuil0,935

Scores du classifieur distillé par catégorie (deux têtes)

CatégorieCodexGemma
Métarecherche0,0010,004
Méta-épidémiologie (sens strict)0,0010,000
Méta-épidémiologie (sens large)0,0010,001
Bibliométrie0,0000,000
Études des sciences et des technologies0,0050,001
Communication savante0,0030,003
Science ouverte0,0010,005
Intégrité de la recherche0,0020,004
Charge utile insuffisante (le modèle a refusé de juger)0,2790,219

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.

Tête enseignante Opus0,480
Tête enseignante GPT0,559
Écart entre enseignants0,079 · la distance entre les deux têtes enseignantes sur ce seul travail
Statut de validationscore_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 découle

Classification

machine, non validée

Prédiction automatique; un appel candidat d’une seule source (Gemma direct ou Codex distillé), pas un consensus.

Les modèles n’ont appliqué aucune catégorie : rien dans la taxonomie ne correspondait à ce travail.
Devis d'étudeSans objet
Domainenon disponible
GenreAutre

Le détail, modèle par modèle et score par score, se trouve en fin de page sous « Comment cette classification a été obtenue ».

En bref

Citations0
Publié2012
Routes d'admission1
Résumé présentoui

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