MétaCan
Menu
Back to cohort
Record W2098168844 · doi:10.1093/hsw/31.4.266

Organizational Characteristics Influencing Nursing Home Social Service Directors' Qualifications: A National Study

2006· article· en· W2098168844 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

VenueHealth & Social Work · 2006
Typearticle
Languageen
FieldHealth Professions
TopicGeriatric Care and Nursing Homes
Canadian institutionsBaycrest Hospital
Fundersnot available
KeywordsSocial workNursingService (business)Work (physics)MedicineGerontologyPsychologyFamily medicineManagementPolitical scienceBusinessEngineeringMarketingLaw

Abstract

fetched live from OpenAlex

This research sought to identify organizational characteristics associated with the amount of professional qualifications among a nationally representative sample of nursing home social service directors. A self-administered survey was sent to directors in 675 facilities randomly sampled from a federal database, excluding facilities with fewer than 120 beds that are not required to staff a full-time social worker. The response rate was 45 percent (N = 299). Univariate results showed that most respondents possessed a social work degree, most lacked licensure, and few were clinically supervised. A multiple regression analysis found that nonprofit, independently owned facilities in rural areas staffed social service directors who were significantly more qualified than directors in for-profit, chain-affiliated facilities in urban and suburban areas. Facilities with fewer psychosocial deficiencies and higher occupancy rates employed social service directors with greater qualifications. The implications of these findings for social work education, practice, policy, and research are discussed.

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 categoriesMeta-epidemiology (narrow), Science and technology studies
Consensus categoriesnone
DomainCandidate signal: none · Consensus signal: none
Study designCandidate signal: Observational · Consensus signal: Observational
GenreCandidate signal: Empirical · Consensus signal: Empirical
Teacher disagreement score0.562
Threshold uncertainty score1.000

Codex and Gemma teacher scores by category

CategoryCodexGemma
Metaresearch0.0010.000
Meta-epidemiology (narrow)0.0000.000
Meta-epidemiology (broad)0.0000.000
Bibliometrics0.0000.002
Science and technology studies0.0070.000
Scholarly communication0.0000.000
Open science0.0000.000
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 head0.055
GPT teacher head0.419
Teacher spread0.364 · 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