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Table 3 Concepts in policy literature. Concepts are divided as ‘Name-like’ or ‘Word-like’. ‘Name-like’ identifies proper names, e.g., PNG

From: Mainstreaming gender and promoting intersectionality in Papua New Guinea’s health policy: a triangulated analysis applying data-mining and content analytic techniques

Name-like

Count

Relevancea

PNG

811

62%

Government

321

25%

HIV

250

19%

PNGDSP

186

14%

AIDS

90

07%

Word-like

Count

Relevance

Health

1301

100%

Research

706

54%

Services

379

29%

Development

370

28%

Sector

348

27%

Levels

326

25%

Areas

297

23%

System

295

23%

Policy

250

19%

Including

236

18%

Service

233

18%

Delivery

216

17%

Capacity

206

16%

People

203

16%

Provide

194

15%

Implementation

191

15%

National

185

14%

Support

182

14%

Rural

181

14%

Quality

175

13%

Access

175

13%

Public

171

13%

Care

169

13%

Facilities

168

13%

Promotion

166

13%

Information

166

13%

Community

165

13%

Population

163

13%

Strategies

155

12%

Resources

155

12%

Important

152

12%

Education

149

11%

Ensure

144

11%

Use

144

11%

Economic

141

11%

Key

138

11%

Management

132

10%

Country

130

10%

Effective

129

10%

International

127

10%

Private

124

10%

Needs

119

09%

Available

117

09%

Required

114

09%

Impact

112

09%

Planning

105

08%

Process

104

08%

Based

102

08%

Developed

99

08%

Include

98

08%

Drugs

93

07%

Workers

92

07%

Provided

91

07%

Countries

91

07%

Cost

90

07%

Relevant

79

06%

  1. aFrequency of segments of text coded with the concept, relative to the most frequently occurring concept